676 research outputs found
Temperature-dependent morphology-electron mobility correlations of naphthalene diimide-indacenodithiophene copolymers prepared via direct arylation polymerization
A series of defect-free n-type copolymers poly(naphthalene diimide-alt-indacenodithiophene) P(NDI-IDT) comprising alternating naphthalene diimide (NDI) and indacenodithiophene (IDT) units is prepared using atom-economic direct arylation polycondensation (DAP)
Recommended from our members
Interdot Lead Halide Excess Management in PbS Quantum Dot Solar Cells
Light-harvesting devices made from lead sulfide quantum dot (QD) absorbers are one of the many promising technologies of third-generation photovoltaics. Their simple, solution-based fabrication, together with a highly tunable and broad light absorption makes their application in newly developed solar cells, particularly promising. In order to yield devices with reduced voltage and current losses, PbS QDs need to have strategically passivated surfaces, most commonly achieved through lead iodide and bromide passivation. The interdot spacing is then predominantly filled with residual amorphous lead halide species that remain from the ligand exchange, thus hindering efficient charge transport and reducing device stability. Herein, it is demonstrated that a post-treatment by iodide-based 2-phenylethlyammonium salts and intermediate 2D perovskite formation can be used to manage the lead halide excess in the PbS QD active layer. This treatment results in improved device performance and increased shelf-life stability, demonstrating the importance of interdot spacing management in PbS QD photovoltaics
Recommended from our members
Highly efficient modulation doping: A path toward superior organic thermoelectric devices
We investigate the charge and thermoelectric transport in modulation-doped large-area rubrene thin-film crystals with different crystal phases. We show that modulation doping allows achieving superior doping efficiencies even for high doping densities, when conventional bulk doping runs into the reserve regime. Modulation-doped orthorhombic rubrene achieves much improved thermoelectric power factors, exceeding 20 ÎŒW mâ1 Kâ2 at 80°C. Theoretical studies give insight into the energy landscape of the heterostructures and its influence on qualitative trends of the Seebeck coefficient. Our results show that modulation doping together with high-mobility crystalline organic semiconductor films is a previosly unexplored strategy for achieving high-performance organic thermoelectrics
Author Correction: Traps and transport resistance are the next frontiers for stable non-fullerene acceptor solar cells.
Stability is one of the most important challenges facing material research for organic solar cells (OSC) on their path to further commercialization. In the high-performance material system PM6:Y6 studied here, we investigate degradation mechanisms of inverted photovoltaic devices. We have identified two distinct degradation pathways: one requires the presence of both illumination and oxygen and features a short-circuit current reduction, the other one is induced thermally and marked by severe losses of open-circuit voltage and fill factor. We focus our investigation on the thermally accelerated degradation. Our findings show that bulk material properties and interfaces remain remarkably stable, however, aging-induced defect state formation in the active layer remains the primary cause of thermal degradation. The increased trap density leads to higher non-radiative recombination, which limits the open-circuit voltage and lowers the charge carrier mobility in the photoactive layer. Furthermore, we find the trap-induced transport resistance to be the major reason for the drop in fill factor. Our results suggest that device lifetimes could be significantly increased by marginally suppressing trap formation, leading to a bright future for OSC
Reinventing grounded theory: some questions about theory, ground and discovery
Grounded theoryâs popularity persists after three decades of broad-ranging critique. In this article three problematic notions are discussedââtheory,â âgroundâ and âdiscoveryââwhich linger in the continuing use and development of grounded theory procedures. It is argued that far from providing the epistemic security promised by grounded theory, these notionsâembodied in continuing reinventions of grounded theoryâconstrain and distort qualitative inquiry, and that what is contrived is not in fact theory in any meaningful sense, that âgroundâ is a misnomer when talking about interpretation and that what ultimately materializes following grounded theory procedures is less like discovery and more akin to invention. The procedures admittedly provide signposts for qualitative inquirers, but educational researchers should be wary, for the significance of interpretation, narrative and reflection can be undermined in the procedures of grounded theory
Weighing the Giants - I. Weak-lensing masses for 51 massive galaxy clusters: project overview, data analysis methods and cluster images
This is the first in a series of papers in which we measure accurate
weak-lensing masses for 51 of the most X-ray luminous galaxy clusters known at
redshifts 0.15<z<0.7, in order to calibrate X-ray and other mass proxies for
cosmological cluster experiments. The primary aim is to improve the absolute
mass calibration of cluster observables, currently the dominant systematic
uncertainty for cluster count experiments. Key elements of this work are the
rigorous quantification of systematic uncertainties, high-quality data
reduction and photometric calibration, and the "blind" nature of the analysis
to avoid confirmation bias. Our target clusters are drawn from RASS X-ray
catalogs, and provide a versatile calibration sample for many aspects of
cluster cosmology. We have acquired wide-field, high-quality imaging using the
Subaru and CFHT telescopes for all 51 clusters, in at least three bands per
cluster. For a subset of 27 clusters, we have data in at least five bands,
allowing accurate photo-z estimates of lensed galaxies. In this paper, we
describe the cluster sample and observations, and detail the processing of the
SuprimeCam data to yield high-quality images suitable for robust weak-lensing
shape measurements and precision photometry. For each cluster, we present
wide-field color optical images and maps of the weak-lensing mass distribution,
the optical light distribution, and the X-ray emission, providing insights into
the large-scale structure in which the clusters are embedded. We measure the
offsets between X-ray centroids and Brightest Cluster Galaxies in the clusters,
finding these to be small in general, with a median of 20kpc. For offsets
<100kpc, weak-lensing mass measurements centered on the BCGs agree well with
values determined relative to the X-ray centroids; miscentering is therefore
not a significant source of systematic uncertainty for our mass measurements.
[abridged]Comment: 26 pages, 19 figures (Appendix C not included). Accepted after minor
revisio
Recommended from our members
DNA methylation-based classification of central nervous system tumours.
Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology
- âŠ