Characterisation of performance limiting defects in photovoltaic devices using electroluminescence and related techniques

Solar cells allow the energy from the sun to be converted into electrical energy; this makes solar energy an environmentally friendly, sustainable alternative to fossil fuel energy sources. Solar cells are connected together in a photovoltaic (PV) module to provide the higher current, voltage and power outputs necessary for electrical applications. However, the performance of PV modules can limited by the degradation and defects. PV modules can be characterised using various opto-electronic techniques, each providing information about the performance of the module. The current-voltage (I-V) characteristic curve of a module being the most commonly used characterisation technique. The I-V curve is typically measured in outdoor, fully illuminated, conditions. This allows performance parameters such as short circuit current (ISC), open circuit voltage (VOC) and maximum power (PMAX) to be determined. However, it can be difficult to determine the root cause of the performance drop from the I-V curve alone. Electroluminescence (EL) is a module characterisation technique that allows defects and failures in PV modules to be successfully identified. This study investigates the characterisation of solar cells and photovoltaic modules using EL. EL occurs when a solar cell or module is forward biased and the injected electron-hole pairs recombine radiatively. The intensity of the emitted EL is related the applied voltage and the material properties. EL imaging is a useful characterisation technique in identifying module defects and failures. Defects such as micro-cracks, broken contact fingers and fractures are detected in EL images as well as material features such as grain boundaries. The common defects in crystalline silicon are catalogued and the possible causes are discussed. An experimental setup was developed in order to systematically take a high resolution EL image of every cell in the module and record the applied voltage and current. This produces a very detailed, clear, image of each cell with a pixel size in the micrometre range. This process is time consuming to acquire an EL image of an entire module so alternatively a different setup can be used and an EL image of a whole module can be captured in a single frame with an increased pixel size in the millimetre range. For EL imaging a silicon charge-coupled device (CCD) camera was used because it has very good spatial resolution however this sensor is only sensitive to wavelength in the range of 300-1200 nm. There is an overlap in wavelengths from about 900 to 1100 nm allowing the EL emitted from silicon solar cells to be detected. In conjunction with the high-resolution EL system an image processing program was developed to crop, adjust and align the images so only the relevant cell was included. This program also automatically detects certain defects that have a regular shape. Micro-cracks, broken fingers and striation rings are automatically identified. The program has an adjustable sensitivity to identify small or large defects. Defective cells are distinguished from undamaged cells by comparing the binary images to the ideal, undamaged cell. The current-voltage curves and the performance parameters of modules were compared with the EL images in order to discuss and identify power limiting defects. Features that remove significant portions of the cell from electrical contact such as micro-cracks are shown to have a larger effect of the performance of the module. Other features such as broken contact fingers, contact forming failures and striation rings do not significantly lower the performance of the module. Thus an understanding of how different features affect the module performance is important in order to correctly interpret the EL results. The intensity of the luminescence emitted is related to the applied voltage and the quantum efficiency of the cell material. The spectrum of the emitted luminescence was modelled and related to the recombination properties of the cell such as surface recombination velocity and minority carrier diffusion length/lifetime. In this study the emitted spectrum was modelled and the effects of recombination properties of the cell on the emitted spectrum were examined. The spectrum of the detected EL was modelled, dependent on the sensitivity of the camera, the transmission of the filters and the emitted photon flux. The integration of short-pass filters into the experimental setup in order to isolate short-wavelength luminescence was discussed. There is a proportional relationship between the intensity of the emitted EL and the local junction voltage. Resistive losses like series and shunt resistances lower the applied voltage and thus affect the EL image. The voltage dependence was assessed by comparing EL images taken at different applied biases. Analysis of the variation in EL intensity with voltage was successful in determining the origin of certain features in an EL image. Certain defects, those that are related to series resistance or shunting are highly voltage dependent. When a feature has little or no dependence on voltage then the defect could be in the laminate layers and not in the cell material. The results of this study allow for in-depth analysis of the defects found in PV modules using the high resolution EL imaging system and the image processing routine. The development of an image processing routine allows the interpretation of the EL image to be done automatically, resulting in a faster and more efficient process. By understanding the defects visible in the EL image, the test is more meaningful and allows the results to be used to predict module performance and potential failures

Characterization of cell mismatch in photovoltaic modules using electroluminescence and associated electro-optic techniques

Solar cells allow the energy from the sun to be converted into electrical energy; this makes solar energy much more environmentally friendly than fossil fuel energy sources. These solar cells are connected together in a photovoltaic (PV) module to provide the higher current, voltage and power outputs necessary for electrical applications. However, the performance of the PV module is limited by the performance of the individual cells. Cell mismatch occurs when some cells are damaged or shaded and produce lower current output than the other cells in the series connected string. The cell mismatch lowers the module performance and can result in further damage as the weak cells are reverse biased and dissipate heat. Bypass diodes can be connected into the module to increase the module current output and prevent further damage. Since cell mismatch results in a significant decrease in the performance of deployed modules it is important to fully understand and characterise its effect on PV modules. PV modules can be characterised using various techniques, each providing important information about the performance of the module. Most commonly the current-voltage (I-V) characteristic curve of a module is measured in outdoor, fully illuminated conditions. This allows performance parameters such as short circuit current (Isc), open circuit voltage (Voc) and maximum power (Pmax) to be determined. In addition to this the shape of the curve allows device parameters like series and shunt resistances to be determined using parameter extraction algorithms like Particle Swarm Optimisation (PSO). The extracted parameters can be entered into the diode equation to model the I-V curve of the module. The I-V characteristic of the module can also be used to identify poor current producing cells in the module by using the worst-case cell determination method. In this technique a cell is shaded and the greater the drop in current in the whole module the better the current production of the shaded cell. The photoresponse of cells in a module can be determined by the Large-area Light Beam Induced Current (LA-LBIC) technique which involves scanning a module with a laser beam and recording the current generated. Electroluminescence (EL) is emitted by a forward biased PV module and is used to identify defects in cell material. Defects such as cracks and broken fingers can be detected as well as material features such as grain boundaries. These techniques are used to in conjunction to characterise the modules used in this study. The modules investigated in this study each exhibit cell mismatch resulting from different causes. Each module is characterised using a combination of characterisation techniques which allows the effect of cell mismatch be investigated. EL imaging enabled cracks and defects, invisible to the naked eye, to be detected allowing the reduced performance observed in I-V curves to be explained. It was seen that the cracked cells have a significant effect on the current produced by a string, while the effect of delaminated areas is less severe. Hot spots are observed on weak cells indicating they are in reverse bias conditions and will degrade further with time. PSO parameter extraction from I-V curves revealed that the effect of module degradation of device parameters like series and shunt resistances. A module with cracked cells and degradation of the antireflective coating has low shunt resistance indicating current losses due to shunting. Similar shunting is observed in a module with delamination and moisture ingress. The extracted parameters are used to simulate the I-V curves of modules with reasonable fit. The fit could be improved around the “knee” of the I-V curve by improving the methods of parameter extraction. This study has shown the effects of cell mismatch on the performance and I-V curves of the PV modules. The different causes of cell mismatch are discussed and modules with different cell configuration and damage are characterised. The characterisation techniques used on each module provide information about the photoresponse, current generation, material properties and cell defects. A comprehensive understanding of these techniques allows the cell mismatch in the modules to be fully characterized

Revisiting funeral recordings during and beyond the COVID-19 pandemic in the UK

Peer reviewedPublisher PD

Hybrid funerals : how online attendance facilitates and impedes participation

This research was funded by the Economic and Social Research Council (ESRC), as part of UK Research and Innovation’s rapid response to Covid-19. Grant number: [ES/V017047/1].Peer reviewedPublisher PD

Why does funeral attendance matter? : Revisiting 'Configurational Eulogies' in light of the COVID-19 pandemic in the UK

Open Access via the Taylor & Francis Agreement Acknowledgements The authors thank Paul Kefford and Imogen Jones and two anonymous reviewers for their helpful feedback on earlier drafts of this paper. Funding This research was funded by the Economic and Social Research Council (ESRC), as part of UK Research and Innovation’s rapid response to Covid-19. Grant number: [ES/V017047/1].Peer reviewedPublisher PD

The role of l-arabinose metabolism for <i>Escherichia coli</i> O157:H7 in edible plants

International audienceArabinose is a major plant aldopentose in the form of arabinans complexed in cell wall polysaccharides or glycoproteins (AGP), but comparatively rare as a monosaccharide. l -arabinose is an important bacterial metabolite, accessed by pectolytic micro-organisms such as Pectobacterium atrosepticum via pectin and hemicellulose degrading enzymes. However, not all plant-associated microbes encode cell-wall-degrading enzymes, yet can metabolize l -arabinose, raising questions about their use of and access to the glycan in plants. Therefore, we examined l -arabinose metabolism in the food-borne pathogen Escherichia coli O157:H7 (isolate Sakai) during its colonization of plants. l -arabinose metabolism ( araBA ) and transport ( araF ) genes were activated at 18 °C in vitro by l -arabinose and expressed over prolonged periods in planta . Although deletion of araBAD did not impact the colonization ability of E. coli O157:H7 (Sakai) on spinach and lettuce plants (both associated with STEC outbreaks), araA was induced on exposure to spinach cell-wall polysaccharides. Furthermore, debranched and arabinan oligosaccharides induced ara metabolism gene expression in vitro , and stimulated modest proliferation, while immobilized pectin did not. Thus, E. coli O157:H7 (Sakai) can utilize pectin/AGP-derived l -arabinose as a metabolite. Furthermore, it differs fundamentally in ara gene organization, transport and regulation from the related pectinolytic species P. atrosepticum , reflective of distinct plant-associated lifestyles

Surface proteins of Shiga toxin-producing Escherichia coli mediate association with milk fat globules in raw milk

IntroductionBy adhering to host cells and colonizing tissues, bacterial pathogens can successfully establish infection. Adhesion is considered the first step of the infection process and bacterial adhesion to anti-adhesive compounds is now seen as a promising strategy to prevent infectious diseases. Among the natural sources of anti-adhesive molecules, the membrane of milk fat globules (MFGs) is of interest because of its compositional diversity of proteins and glycoconjugates. However, few studies have focused on the bacterial molecules involved in MFG- mediated inhibition of bacterial adhesion to enterocytes.MethodsWe used three pathogenic Shiga toxin-producing Escherichia coli (STEC) strains (O26:H11 str. 21765, O157:H7 str. EDL933, and O103:H3 str. PMK5) as models to evaluate whether STEC surface proteins are involved in the affinity of STEC for MFG membrane proteins (MFGMPs). The affinity of STEC for MFGMPs was assessed both indirectly by a natural raw milk creaming test and directly by an adhesion test. Mass spectrometry was used to identify enriched STEC proteins within the protein fraction of MFGMs. Bacterial mutants were constructed and their affinity to MFGs were measured to confirm the role of the identified proteins.ResultsWe found that free STEC surface proteins inhibit the concentration of the pathogen in the MFG-enriched cream in a strain-dependent manner. Moreover, the OmpA and FliC proteins were identified within the protein fraction of MFGMs. Our results suggest that FliC protein participates in STEC adhesion to MFGMPs but other STEC molecules may also participate.DiscussionFor the first time, this study highlighted, the involvement of STEC surface proteins in the affinity for MFGs. The mechanism of STEC-MFG association is still not fully understood but our results confirm the existence of receptor/ligand type interactions between the bacteria and MFGs. Further studies are needed to identify and specify the molecules involved in this interaction. These studies should consider the likely involvement of several factors, including adhesion molecules, and the diversity of each STEC strain

Exploring the relative lack of impact of research on ‘ability grouping’ in England: a discourse analytic account

Grouping students by ‘ability’ is a topic of long-standing contention in English education policy, research and practice. While policy-makers have frequently advocated the practice as reflecting educational ‘standards’, research has consistently failed to find significant benefits of ‘ability’ grouping; and indeed has identified disadvantages for some (low-attaining) pupil groups. However, this research evidence has apparently failed to impact on practice in England. This article, contextualised by the authors’ interests in education and social inequality, seeks to do two things. First, it provides a brief analysis of the existing research evidence on the impact of ‘ability’ grouping, with particular reference to socio-economic inequality, identifying seven different explanations for the poorer progress of pupils in low sets that emerge from the literature. Second, it applies Foucaultian ‘analysis of discourse’ to propose potential explanations for the apparent lack of traction of existing research with policy and practice, arguing that practices of ‘ability grouping’ reflect cultural investments in discourses of ‘natural order’ and hierarchy, with particular resonance for the discursive and political habitus of middle-class parents. The authors postulate that investing in a powerful counter-discourse of enlightenment science, illustrated via their current randomised control trial of different approaches to pupil grouping, may offer a means to challenge hegemonic discourses that underpin current classroom practice

Being Ready to Treat Ebola Virus Disease Patients

As the outbreak of Ebola virus disease (EVD) in West Africa continues, clinical preparedness is needed in countries at risk for EVD (e.g., United States) and more fully equipped and supported clinical teams in those countries with epidemic spread of EVD in Africa. Clinical staff must approach the patient with a very deliberate focus on providing effective care while assuring personal safety. To do this, both individual health care providers and health systems must improve EVD care. Although formal guidance toward these goals exists from the World Health Organization, Medecin Sans Frontières, the Centers for Disease Control and Prevention, and other groups, some of the most critical lessons come from personal experience. In this narrative, clinicians deployed by the World Health Organization into a wide range of clinical settings in West Africa distill key, practical considerations for working safely and effectively with patients with EVD