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The properties of the encapsulant are critical to the long-term performance of photovoltaic (PV) modules under the influence of sunlight including UV, elevated temperature, humidity and diffusion of oxygen. Encapsulation process represents a bout 40% of the whole PV module cost. The introduction of new non-EVA encapsulant material type "Low-Cost, High-Performance" should provide a solution to outdoor yellowing degradation problems. The emerging encapsulant materials exhibit a good compatibility with emerging PV solar cells for long term durability. This new generation of encapsulant materials has the advantage to improve e the PV module performances and long term durability for specific climate like desert regions. This scientific contribution presents an overview of the different encapsulant materials currently on the market, the general requirements of the emerging encapsulant materials and characterizations techniques for degradation, diagnostic and reliability lifetime estimation in the framework of Algerian renewable energy strategy.
Photon upconversion upon 1550 nm excitation is of high relevance for applications in the third biological excitation window, for photovoltaics beyond current limitations, and enables appealing options in the field of glass Fiber telecommunications. Trivalent doped erbium ions (Er3+) are the material of choice for 1550 nm excited upconversion, however, they suffer from a low absorption cross-section and a low brightness. Therefore, the ability of Silicon metasurfaces to provide greatly enhanced electrical near-fields is employed to enable efficient photon upconversion even at low external Illumination conditions. Hexagonally shaped β-NaYF4:Er3+ nanoparticles are placed on large-area silicon metasurfaces designed to convert near-infrared (1550 nm) to visible light. More than 2400-fold enhanced photon upconversion luminescence is achieved by using this metasurface instead of a planar substrate.
With the aid of optical simulations based on the finite-element method, this result is attributed to the coupling of the excitation source with metasurface resonances at appropriate incident angles. Analysis of the excitation power density dependence of upconversion luminescence and red-to-green-emission ratios enables the estimation of nanoscale near-field enhancement on the metasurface. The findings permit the significant reduction of required external excitation intensities for photon upconversion of 1550 nm light, opening perspectives in biophotonics, telecommunication, and photovoltaics.
Condensation particle counters (CPCs) are widely used for the measurement of aerosol particle number concentrations in the size range from approximately 3 nm to 3 μm. For an SI-traceable calibration of the size-dependent counting efficiency, which is advisable on a regular basis and required in several applications, Faraday cup aerosol electrometers (FCAEs) are considered to be a suitable SI-traceable reference.While the volumetric aerosol inlet flowrate and the electrical current measurement in FCAEs can be related to respective SI references, inter-comparison exercises for FCAEs are still performed on a regular basis to establish reliable uncertainty budgets and to further investigate the influences of designs and operational parameters on comparability. This is strongly demanded in the international community of metrological institutes and aerosol calibration facilities around the world, which provide CPC calibrations. In the present study, the performance of FCAEs was investigated,using Ag test aerosol particles with a 30 nm particle diameter by varying the inlet flowrates from 0.5 l min−1 to 4 l min−1. From our experimental results, significant deviations were observed in FCAE currents at sample flowrates smaller than 1.5 l min−1. It is recommended that these discrepancies should be quantified before an FCAE is used for CPC calibration at low sample flowrates and small particle sizes in the sub-30 nm size range.
In this paper we propose super resolution measurement and post-processing strategies that can be applied in thermography using laser line scanning. The implementation of these techniques facilitates the separation of two closely spaced defects and avoids the expected deterioration of spatial resolution due to heat diffusion. The experimental studies were performed using a high-power laser as heat source in combination with pulsed thermography measurements (step scanning) or with continuous heating measurements (continuous scanning). Our work shows that laser line step scanning as well as continuous scanning both can be used within our developed super resolution (SR) techniques. Our SR techniques make use of a compressed sensing based algorithm in post- processing, the so-called iterative joint sparsity (IJOSP) approach. The IJOSP method benefits from both - the sparse nature of defects in space as well as from the similarity of each measurement. In addition, we show further methods to improve the reconstruction quality e.g. by simple manipulations in thermal image processing such as by considering the effect of the scanning motion or by using different optimization algorithms within the IJOSP approach. These super resolution image processing methods are discussed so that the advantages and disadvantages of each method can be extracted. Our contribution thus provides new approaches for the implementation of super resolution techniques in laser line scanning thermography and informs about which experimental and post-processing parameters should be chosen to better separate two closely spaced defects.
Laser excited super resolution thermal imaging for nondestructive inspection of internal defects
(2020)
A photothermal super resolution technique is proposed for an improved inspection of internal defects. To evaluate the potential of the laser-based thermographic technique, an additively manufactured stainless steel specimen with closely spaced internal cavities is used. Four different experimental configurations in transmission, reflection, stepwise and continuous scanning are investigated. The applied image post-processing method is based on compressed sensing and makes use of the block sparsity from multiple measurement events. This concerted approach of experimental measurement strategy and numerical optimization enables the resolution of internal defects and outperforms conventional thermographic inspection techniques.
We combine three different approaches to greatly enhance the defect reconstruction ability of active thermographic testing. As experimental approach, laser-based structured illumination is performed in a step-wise manner. As an intermediate signal processing step, the virtual wave concept is used in order to effectively convert the notoriously difficult to solve diffusion-based inverse problem into a somewhat milder wavebased inverse problem. As a final step, a compressed-sensing based optimization procedure is applied which efficiently solves the inverse problem by making advantage of the joint sparsity of multiple blind measurements. To evaluate our proposed processing technique, we investigate an additively manufactured stainless steel sample with eight internal defects. The concerted super resolution approach is compared to conventional thermographic reconstruction techniques and shows an at least four times better spatial resolution.
The embrittlement of metallic alloys by liquid metals leads to catastrophic material failure and severely impacts their structural integrity. The weakening of grain boundaries by the ingress of liquid metal and preceding segregation in the solid are thought to promote early fracture. However, the potential of balancing between the segregation of cohesion-enhancing interstitial solutes and embrittling elements inducing grain boundary decohesion is not understood. Here, we unveil the mechanisms of how boron segregation mitigates the detrimental effects of the prime embrittler, zinc, in a Σ5 [0 0 1] tilt grain boundary in α −Fe (4 at.% Al). Zinc forms nanoscale segregation patterns inducing structurally and compositionally complex grain boundary states. Ab-initio simulations reveal that boron hinders zinc segregation and compensates for the zinc induced loss in grain boundary cohesion. Our work sheds new light on how interstitial solutes intimately modify grain boundaries, thereby opening pathways to use them as dopants for preventing disastrous material failure.
Aiming at the overall negative surface charge of bacteria, a new strategy of antibacterial agents based on large polymer-modified graphene oxide (GO) sheets is assessed. The presented flexible, polycationic Sheets match the size and charge density of the Escherichia coli surface charge density (2 × 1014 cm−2). These matching parameters create an unspecific but very strong bacteria adsorber by multivalent, electrostatic attraction.
Their interaction with bacteria is visualized via atomic force and confocal microscopy and shows that they effectively bind and wrap around E. coli cells, and thereby immobilize them. The incubation of Gram-negative and -positive bacteria (E. coli and methicillin-resistant Staphylococcus aureus, MRSA) with these polycationic sheets leads to the inhibition of proliferation and a reduction of the colony forming bacteria over time.
This new type of antibacterial agent acts in a different mode of Action than classical biocides and could potentially be employed in medicinal, technical, or agriculture applications. The presented microsheets and their unspecific binding of cell interfaces could further be employed as adsorber material for bacterial filtration or immobilization for imaging, analysis, or sensor technologies.
We report on the ferromagnetism of Sn1-xZnxO2 (x < 0.1) hierarchical nanostructures with various morphologies synthesized by a solvothermal route. A room temperature ferromagnetic and paramagnetic response was observed for all compositions, with a maximum in ferromagnetism for x = 0.04. The ferromagnetic behaviour was found to correlate with the presence of zinc on substitutional Sn sites and with a low oxygen vacancy concentration in the samples. The morphology of the nanostructures varied with zinc concentration. The strongest ferromagnetic response was observed in nanostructures with well-formed shapes, having nanoneedles on their surfaces. These nanoneedles consist of (110) and (101) planes, which are understood to be important in stabilizing the ferromagnetic defects. At higher zinc concentration the nanostructures become eroded and agglomerated, a phenomenon accompanied with a strong decrease in their ferromagnetic response. The observed trends are explained in the light of recent computational studies that discuss the relative stability of ferromagnetic defects on various surfaces and the role of oxygen vacancies in degrading ferromagnetism via an increase in free electron concentration.
A systematic study has been carried out to investigate the neutron transmission signal as a function of sample temperature. In particular, the experimentally determined wavelength-dependent neutron attenuation spectra for a martensitic steel at temperatures ranging from 21 to 700°C are compared with simulated data. A theoretical description that includes the Debye–Waller factor in order to describe the temperature influence on the neutron cross sections was implemented in the nxsPlotter software and used for the simulations. The analysis of the attenuation coefficients at varying temperatures shows that the missing contributions due to elastic and inelastic scattering can be clearly distinguished: while the elastically scattered intensities decrease with higher temperatures, the inelastically scattered intensities increase, and the two can be separated from each other by analysing unique sharp features in the form of Bragg edges. This study presents the first systematic approach to quantify this effect and can serve as a basis , for example, to correct measurements taken during in situ heat treatments, in many cases being a prerequisite for obtaining quantifiable results.
Machine learning-assisted equivalent circuit identification for dielectric spectroscopy of polymers
(2024)
Polymers have become indispensable across fields of application, and understanding their structure–property relationships and dynamic behaviour is essential for performance optimization. Polymer membranes, particularly ion exchange membranes, play a crucial role in renewable energy conversion technologies, fuel cells, solar energy conversion, and energy storage. In this context, broadband dielectric spectroscopy (BDS) offers a powerful, non-destructive approach to investigate the electrical response and relaxation dynamics of polymers. These properties are investigated by parametrizing the system’s impedance response in terms of a network of circuit elements, i.e. the electrical equivalent circuit (EEC), whose impedance resembles the one of the system under investigation. However, the determination of the EEC from BDS data is challenging due to system complexity, interdependencies of circuit elements, and researcher biases. In this work, we propose a novel approach that incorporates a convolutional neural network (CNN) model to predict the EEC topology. By reducing user bias and enhancing data analysis, this approach aims to make BDS accessible to both experienced users and those with limited expertise. We show that the combination of machine learning and BDS provides valuable insights into the dynamic behaviour of polymer membranes, thus facilitating the design and characterization of tailored polymers for various applications. We also show that our model outperforms state-of-the-art machine learning methods with a top-5 accuracy of around 80% for predicting the circuit topology and a parameter fitting error as low as 0.05%.
Over the last few years, the Federal Institute for material research (BAM, Berlin) together with the Centre for the Study of Manuscript Cultures (CSMC, University of Hamburg) have initiated a systematic material investigation of black inks produced from Late Antiquity to the Middle Ages (ca. fourth century CE–fourteenth/fifteenth centuries CE), aimed primarily at extending and complementing findings from previous sporadic studies. Part of this systematic investigation has focused on Egyptian Coptic manuscripts, and the present preliminary study is one of its outputs. It centres on a corpus of 45 Coptic manuscripts—43 papyri and 2 ostraca—preserved at the Palau-Ribes and Roca-Puig collections in Barcelona. The manuscripts come from the Monastery of Apa Apollo at Bawit, one of the largest monastic settlements in Egypt between the Late Antiquity and the Early Islamic Period (sixth–eighth centuries CE). The composition of their black inks was investigated in situ using near-infrared reflectography (NIRR) and X-ray fluorescence (XRF). The analyses determined that the manuscripts were written using different types of ink: pure carbon ink; carbon ink containing iron; mixed inks containing carbon, polyphenols and metallic elements; and iron-gall ink. The variety of inks used for the documentary texts seems to reflect the articulate administrative system of the monastery of Bawit. This study reveals that, in contrast to the documents, written mostly with carbon-based inks, literary biblical texts were written with iron-gall ink. The frequent reuse of papyrus paper for certain categories of documents may suggest that carbon-based inks were used for ephemeral manuscripts, since they were easy to erase by abrasion.
Simulation-Assisted Augmentation of Missing Wedge and Region-of-Interest Computed Tomography Data
(2024)
This study reports a strategy to use sophisticated, realistic X-ray Computed Tomography (CT) simulations to reduce Missing Wedge (MW) and Region-of-Interest (RoI) artifacts in FBP (Filtered Back-Projection) reconstructions. A 3D model of the object is used to simulate the projections that include the missing information inside the MW and outside the RoI. Such information augments the experimental projections, thereby drastically improving the reconstruction results. An X-ray CT dataset of a selected object is modified to mimic various degrees of RoI and MW problems. The results are evaluated in comparison to a standard FBP reconstruction of the complete dataset. In all cases, the reconstruction quality is significantly improved. Small inclusions present in the scanned object are better localized and quantified. The proposed method has the potential to improve the results of any CT reconstruction algorithm.
The complex nature of liquid water saturation of polymer electrolyte fuel cell (PEFC) catalyst layers (CLs) greatly affects the device performance. To investigate this problem, we present a method to quantify the presence of liquid water in a PEFC CL using small-angle X-ray scattering (SAXS). This method leverages the differences in electron densities between the solid catalyst matrix and the liquid water filled pores of the CL under both dry and wet conditions. This approach is validated using ex situ wetting experiments, which aid the study of the transient saturation of a CL in a flow cell configuration in situ. The azimuthally integrated scattering data are fitted using 3D morphology models of the CL under dry conditions. Different wetting scenarios are realized in silico, and the corresponding SAXS data are numerically simulated by a direct 3D Fourier transformation. The simulated SAXS profiles of the different wetting scenarios are used to interpret the measured SAXS data which allows the derivation of the most probable wetting mechanism within a flow cell electrode.
The aim of this study is to develop nanometer-thin epoxy-based films on aluminium alloy AA2024-T3 as a model coating system for high resolution corrosion studies. Spin coating was used for the layer-by-layer (LbL) deposition of poly-(ethylenimine) (PEI) and poly([o-cresyl glycidyl ether]-co-formaldehyde) (CNER) bilayers. The film chemistry and the cross-linking process were characterized by means of Fourier-transform infrared spectroscopy (FTIR).
Ellipsometric data confirmed the linear increase of film thickness. The potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) results indicate the improvement of the film barrier properties with increasing film thickness. Mapping of the topography and the volta potential was performed by means of scanning Kelvin probe force microscopy (SKPFM).
The results indicate the presence of a homogeneous film structure, while the intermetallic phases can still be identified below the coating. The SKPFM Analysis confirmed that the model films are suitable for investigation of corrosion processes at the coating/metal interface.
The application of characterization methods with high spatial resolution to the analysis of buried coating/metal interfaces requires the design and use of model systems. Herein, an epoxy-like thin film is used as a model coating resembling the epoxy-based coatings and adhesives widely used in technical applications. Spin coating is used for the deposition of a 30 nm-thin bilayer (BL) composed of poly-(ethylenimine) (PEI) and poly[(o-cresyl glycidyl ether)-co-formaldehyde] (CNER). Fourier-transform infrared spectroscopy (FTIR) results confirm that the exposure of coated AA2024-T3 (AA) samples to the corrosive electrolyte solution does not cause the degradation of the polymer layer. In situ atomic force microscopy (AFM) studies are performed to monitor local corrosion processes at the buried interface of the epoxy-like film and the AA2024-T3 aluminum alloy surface in an aqueous electrolyte solution. Hydrogen evolution due to the reduction of water as the cathodic corrosion reaction leads to local blister formation. Based on the results of the complementary energy-dispersive X-ray spectroscopy (EDX) analysis performed at the same region of interest, most of the hydrogen evolved originates at the vicinity of Mg-containing intermetallic particles.
We introduce herein boron-dipyrromethene (BODIPY) dyes as a new class of fluorophores for the design of reporter dyes for supramolecular host–guest complex formation with cucurbit[7]uril (CB7). The BODIPYs contain a protonatable aniline nitrogen in the meso-position of the BODIPY chromophore, which was functionalized with known binding motifs for CB7. The unprotonated dyes show low fluorescence due to photoinduced electron transfer (PET), whereas the protonated dyes are highly fluorescent. Encapsulation of the binding motif inside CB7 positions the aniline nitrogen at the carbonyl rim of CB7, which affects the pKa value, and leads to a host-induced protonation and thus to a fluorescence increase. The possibility to tune binding affinities and pKa values
is demonstrated and it is shown that, in combination with the beneficial photophysical properties of BODIPYs, several new applications of host–dye reporter pairs can be implemented. This includes indicator displacement assays with favourable absorption and
emission wavelengths in the visible spectral region, fluorescence correlation spectroscopy, and noncovalent surface functionalization
with fluorophores.
Additive manufacturing offers a range of novel applications. However, the manufacturing process is complex and the production of almost defect-free parts with high reliability and durability is still a challenge. Thermography is a valuable tool for process surveillance, especially in metal additive manufacturing processes. The high process temperatures allow one to use cameras usually operating in the visible spectral range. Here, we compare the results of measurements during the manufacturing process of a commercial laser metal deposition setup using a mid wavelength infrared camera with those from a short wavelength infrared camera and those from a visual spectrum high-speed camera with band pass filter in the near infrared range.
Mass spectrometry-based proteomics provides a holistic snapshot of the entire protein set of living cells on a molecular level. Currently, only a few deep learning approaches exist that involve peptide fragmentation spectra, which represent partial sequence information of proteins. Commonly, these approaches lack the ability to characterize less studied or even unknown patterns in spectra because of their use of explicit domain knowledge. Here, to elevate unrestricted learning from spectra, we introduce ‘ad hoc learning of fragmentation’ (AHLF), a deep learning model that is end-to-end trained on 19.2 million spectra from several phosphoproteomic datasets. AHLF is interpretable, and we show that peak-level feature importance values and pairwise interactions between peaks are in line with corresponding peptide fragments. We demonstrate our approach by detecting post-translational modifications, specifically protein phosphorylation based on only the fragmentation spectrum without a database search. AHLF increases the area under the receiver operating characteristic curve (AUC) by an average of 9.4% on recent phosphoproteomic data compared with the current state of the art on this task. Furthermore, use of AHLF in rescoring search results increases the number of phosphopeptide identifications by a margin of up to 15.1% at a constant false discovery rate. To show the broad applicability of AHLF, we use transfer learning to also detect cross-linked peptides, as used in protein structure analysis, with an AUC of up to 94%.
In recent years, thermoextraction/desorption-gas chromatography/mass spectrometry (TED-GC/MS) has been developed as a rapid detection method for the determination of microplastics (MP) mass contents in numerous environmentally relevant matrices and, in particular, for the measurement of polymers in water samples without time-consuming sample preparation. The TED-GC/MS method was applied to investigate a typical European municipal wastewater system for possible MP masses. Such investigations are important in view of the recent revision of the Urban Wastewater Treatment Directive. Four different representative sampling sites were selected: greywater (domestic wastewater without toilet), combined sewer, and influent and effluent of a wastewater treatment plant (WWTP). All samples were collected by fractional filtration. Filtration was carried out over mesh sizes of 500, 100, 50, and in some cases, 5 µm. Polyethylene (PE), polypropylene (PP), and polystyrene (PS) were detected in all samples, with the PE fraction dominating in all cases. Styrene-butadiene rubber which serves as an indication of tire abrasion, was only found in the influent of the WWTP. The highest MP mass contents were found in the combined sewer, so MP can become a source of pollution during heavy rain events when the capacity limits of the effluent are reached, and the polluted effluent is released uncontrolled into the environment. Based on the studies, MP retention from the WWTP could be estimated to be approximately 96%. Few trends in polymer type or mass contents were detected within the different fractions of the samples or when comparing samples to each other.