Resultados de investigación

Introducing quantum dots (QDs) as the active element of an optoelectronic device demands its incorporation in the shape of interconnected arrays that allow for some degree of electronic coupling in order to inject/extract charge carriers. In doing so, beyond reducing the degree of quantum confinement, carriers are exposed to an enhanced defect landscape as they can access adjacent QDs, which is at the origin of the strong reduction of photoluminescence observed in QD solids when compared to that of the isolated QDs. In this work we demonstrate how a proper defect passivating strategy or atmospheric treatment can greatly enhance charge diffusion in a QD film, needed for an optimal carrier injection/extraction demanded for optoelectronic applications, and also improved its stability against external radiation. From a fundamental perspective, we provide evidence showing that trap density distribution, rather than QD size distribution, is mostly responsible for the observed variations in emission decay rates present in the QD networks under analysis., File List: (Folder > File.txt) Figure 1 Figure_1b(norm. Abs).txt Figure_1c(PL).txt Figure_1d(norm. TRPL).txt Figure_1e(norm. PL during CW irradiation).txt Figure 2 Figure_2a (TRPL_5%_N2_PMMA).txt Figure_2b (TRPL_20%_N2_PMMA).txt Figure_2c (PL_CW_PMMA).txt Figure_2d (TRPL_5%_N2_O2).txt Figure_2e (TRPL_20%_N2_O2).txt Figure_2f (PL_CW_O2).txt Figure_2g (TRPL_5%_N2_Air).txt Figure_2h (TRPL_20%_N2_Air).txt Figure_2i (PL_CW_Air).txt Figure 3 Figure_3a (TRPL_Fit_5%).txt Figure_3b (DecayRate_Distributions_5%_sample).txt Figure_3c (Width_Average_DecayRateDistribution).txt, Peer reviewed

Accurate quantification of efficiency enables rigorous comparison between different photoluminescent materials, providing an optimization path critical to the development of next-generation light sources. Persistent luminescent materials exhibit delayed and long-lasting luminescence due to the temporary storage of optical energy in engineered structural defects. Although these materials have recently gained attention for their potential in a wide range of applications, from smart lighting to in vivo imaging, standard characterization methods do not provide a universal comparison of phosphor performance, making it difficult to assess the efficiency of the different processes involved in afterglow. In this work we establish a protocol to obtain the emission quantum yield of persistent phosphors. We determine the persistent and total luminescence quantum yields by considering the ratio of photons emitted in the afterglow and during charging to those absorbed. The method is first applied to transparent single crystals of the most common persistent phosphors, such as SrAl2O4:Eu2+,Dy3+ and Y3Al2Ga3O12:Ce3+,Cr3+. The versatility of our methodology is then demonstrated by quantifying the quantum yield of a thin film based on ZnGa2O4:Cr3+ persistent luminescent nanoparticles, which are commonly used for in vivo imaging. We confirm the high efficiency of strontium aluminate and reveal a strong dependence of the obtained values on the illumination conditions, highlighting a trade-off between efficiency and brightness, which opens the door to precise optimization of the charging conditions for each material and application. Our results contribute to the development of standard characterization protocols for the analysis of the mechanisms governing afterglow, as well as the assessment of the overall efficiency of the process. Such achievements enable a rigorous comparison of the performance of different persistent materials, allowing for optimization routes beyond the usual trial-and-error approach., This project has received funding from the BBVA Foundation Leonardo Grant for Physics Researchers 2023, and by Grant EUR2023-143467 funded by MICIU/AEI/ 10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. V.C. acknowledges Junta de Andalucía for financial support (POSTDOC_21_00694)., File List: - Fig1b_KineticScansSAOEuDy.txt : Time (s, column 1), normalized intensity kinetic scans of empty sphere at 400 nm used to calculate Abs (column 2), SAO:Eu,Dy at 400 nm used to calculate Abs (column 3) and SAO:Eu,Dy at 524 nm (column 4). - Fig1c_PersLSpectrumSAOEuDy.txt : Wavelength (nm, column 1), normalized PersL intensity of SAO:Eu,Dy (column 2). - Fig1d_LumSpectrumSAOEuDy.txt : Wavelength (nm, column 1), normalized Lum intensity of SAO:Eu,Dy (column 2). - Fig2a_QYSAOEuDyChargingTime.txt : Charging time (s, column 1), LumQY of SAO:Eu,Dy (column 2), error of LumQY of SAO:Eu,Dy (column 3), PersLQY of SAO:Eu,Dy (column 4) and error of PersLQY of SAO:Eu,Dy (column 5). - Fig2b_ChargingKineticSAOEuDy.txt : Wavelength (nm, column 1), normalized Lum intensity of SAO:Eu,Dy (column 2). - Fig3c_SpectraZGOCr.txt : Wavelength (nm, column 1), normalized Lum intensity of ZGO:Cr (column 2), Wavelength (nm, column 3) and normalized PersL intensity of ZGO:Cr (column 4). - Fig3d_KineticScansZGOCr.txt : Time (s, column 1), normalized intensity kinetic scans of empty sphere at 270 nm used to calculate Abs (column 2), ZGO:Cr at 260 nm used to calculate Abs (column 3) and ZGO:Cr at 696 nm (column 4). - Fig3e_PersLESpectrumZGOCr.txt : Wavelength (nm, column 1) and normalized PersLE intensity of ZGO:Cr (column 2). - Fig4a_IntegratedPersLTemperature.txt : Time after excitation (s, column 1), normalized integrated intensity of ZGO:Cr at RT after excitation at 270 nm (column 2), normalized integrated intensity of ZGO:Cr after excitation at 270 nm with heating at 85 ºC (column 3), Time after excitation (s, column 4), normalized integrated intensity of ZGO:Cr at RT after excitation at 330 nm (column 5), normalized integrated intensity of ZGO:Cr after excitation at 330 nm with heating at 85 ºC (column 6), normalized integrated intensity of SAO:Eu,Dy at RT after excitation at 400 nm (column 7), normalized integrated intensity of SAO:Eu,Dy after excitation at 400 nm with heating at 85 ºC (column 8)., Peer reviewed

SEM image of the tubular structures, TEM images of the nanotubes, measured interplanar spacings in tubular structures, TEM images of a LaS(Te)-TaS2(Te) nanotube, EDS spectra recorded from the nanotubes, HR-STEM micrographs of the LaS(Se)-TaS2(Se) nanotubes, EDS spectrum recorded from a LaS(Se)-TaS2(Se) nanotubes, HR-STEM micrographs of the HoS(Se)-TaS2(Se) nanotubes, HR-STEM and SR-EELS studies of one HoS(Se)-TaS2(Se) nanotube., Peer reviewed

Félix Balima et al., Supplementary experimental procedures and characterizations are included., Peer reviewed

Figures S1 and S2 and Table S1., Peer reviewed

Crystallographic data (powder) of the tetragonal and orthorhombic crystal structures for La1.5Ca0.5CoO4.02. Comparison between the modulus and imaginary part of the FT of the k-weighted polarized EXAFS spectra and best fits of La1.5Ca0.5CoO4.02 for in-plane and out-of-plane configurations at room temperature and best-fit structural parameters for the second coordination shells obtained from fitted polarization-dependent k-weighted EXAFS spectra at room temperature for the La2–xAxCoO4±δ (A = Sr, Ca) single crystals., Peer reviewed

Arbuscular mycorrhizas (AM) are one of the most frequent mutualisms in terrestrial ecosystems where fungi colonized plant roots. This dataset comprises information on the presence and abundance of different AM fungal taxa, in the form of virtual taxa, in woody plant species of two Mediterranean natural areas of South Spain. The data was generated by meta-barcoding the 18S rDNA of AM fungi in plant roots via MiSeq sequencing. This dataset contains more information regarding sampling source regarding the previous version stored in Dryad repository, Ministerio de Ciencia e Innovación: CGL2015-69118-C2-2-P Ministerio de Ciencia e Innovación: PGC2018-100966-B-I00 European Commission, Peer reviewed

-Data to be open with Origin Pro -Data obtained from experiments above as described in paper -Cu and Zn electrodes in Copper and zinc suphate electrolyte as described in the paper, subject to charge discharge cycles, Evaluation of changes in cahrage caapcity, power, current densities in Cu/Zn in neutral pH, in presence of bipolar unwired electrodes in various configurations, Capacities, current densities, CV , impedances and power measurements, Peer reviewed

Lead halide perovskite nanocrystals are attractive for light emitting devices both as electroluminescent and color converting materials, since they combine intense and narrow emissions with good charge injection and transport properties. However, while most perovskite nanocrystals shine at green and red wavelengths, the observation of intense and stable blue emission still remains a challenging target. In this work, we report a method to attain intense and enduring blue emission (470-480 nm), with a photoluminescence quantum yield (PLQY) of 40%, originated from very small CsPbBr3 nanocrystals (diameter<3nm) formed by controllably exposing Cs4PbBr6 to humidity. This process is mediated by the void network of a mesoporous transparent scaffold in which the zero-dimensional Cs4PbBr6 lattice is embedded, which allows the fine control over water adsorption and condensation that determines the optimization of the synthetic procedure and, eventually, the nanocrystal size. Our approach provides a means to attain highly efficient transparent and stable blue light emitting films that complete the palette offered by perovskite nanocrystals for lighting and display applications., Financial support of the Spanish Ministry of Science and Innovation under grant PID2020-116593RB-I00, funded by MCIN/AEI/10.13039/501100011033, and of the Junta de Andalucía under grant P18-RT-2291 (FEDER/UE) and PROYEXCEL00955., File List: f2 f2b.txt; f2c.txt; f3 f3a.txt; f3b.txt; f3d.txt; f3e.txt; f4 f4a.txt; f4c.txt; f4e.txt; f4g.txt; f5 f5a.txt; f5b.txt;, Peer reviewed

[Description of methods used for collection/generation of data] Stem pith tissue samples were extracted with 80% methanol and filtered through a 0.22 µm PTFE membrane to an Eppendorf tube. An aliquot was transferred to a HPLC certified vial. Balanced pools of the total sample extracts were prepared as quality control (QC). Blank extractions were used. All samples were evaporated to dryness, stored at 4° C until analysis, and then dissolved in 80% methanol. Metabolomics profiles were acquired using an ultra‐high‐performance liquid chromatography (UHPLC) system (Thermo Dionex Ultimate 3000 LC) coupled to a quadrupole-time-of-flight mass spectrometer (QTOF-MS) equipped with an electrospray ionization source (ESI) (Bruker Compact; Bruker Daltonics). We measured the analytical samples using three analytical batches, each one con-taining 6 blocks of 10 analytical samples. The analytical samples were randomly assigned to batches and blocks within batches. Blanks were placed at the initial and final positions of each batch and QC samples were evenly distributed bordering the blocks. UHPLC separation was performed with a Inten-sity Solo 2 C18 column (1.7 µm, 2.1× 100 mm; Bruker Daltonics) in gradient elution consisted of 0.1% of formic acid on water (solvent A) and acetonitrile (solvent B) as mobile phase in a 0.4 ml/min flow rate. The elution conditions were: 0 min, 3 % B; 4 min, 3 % B; 16 min, 25 % B; 25min, 80% B; 30 min, 100% B; 32 min, 100% B; and return to initial conditions at 33 min (3% B) for 3 min. Full scan MS data were acquired in both positive and negative ionization modes over the mass range of 100–1200 m/z, and under the following specific conditions: gas flow 9 L min−1; nebuliser pressure 2.6 bar; dry gas 9 L min−1; dry temperature 220 °C. Auto MS/MS fragmentation was performed in pooled samples to facilitate compound identification. After each batch, the MS ion source was cleaned, and the MS was recalibrated. [Methods for processing the data:] We pre-processed the raw MS spectra using the algorithm T-Rex 3D in MetaboScape 4.0 software (Bruker Daltoniks, Germany). Parameters were set to separate measured peaks from background noise and features were grouped across samples and corrected for retention time shifts. After this pre-processing, data were prepared for statistical analysis using Metaboanalyst (Chong et al. 2019). Fea-tures with > 75 % missing data were eliminated and missing data imputation was performed using the KNN (feature-wise) method. Afterwards ANCOVA method was used for batch correction and contam-inants present in blanks were removed. Features with percent relative standard deviation (RSD = SD/mean) > 25 % across QCs samples were removed, as well as uninformative features that presented near-constant values detected by the interquartile range filter (IQR). Then, Pareto scaling was applied to adjust for the disparities in fold differences between the analytes., This dataset belongs to an untargeted metabolomic study to investigate i) the responses in maize pith to the attack of the insect Sesamia nonagrioides under plant colonization by the fungus Fusarium verticillioides; ii) if the response differences could depend on genotype resistance to Fusarium; and iii) to determine metabolites associated to beneficial/detrimental changes of on maize performance. The dataset are LC-MS experimental data for untargeted metabolomics of pith tissues extracts from 8 maize inbred lines genetically diverse with different level of resistance to F. verticillioides infection. Inbred lines were PB130, EP77, A509, EP125, EP42, A637, A630, A239. Experimental treatments were four and labeled as: - Control-Control (CC): no seed inoculation with F. verticillioides and no infestation with S. nonagrioides; - Fusarium-Control (FC): seed inoculation with F. verticillioides and no infestation with S. nonagrioides; - Fusarium-Sesamia (FS): seed inoculation with F. verticillioides and plant infestation with S. nonagrioides; - Control-Sesamia (CS): no seed inoculation with F. verticillioides and plant infestation with S. nonagrioides. Up to six plant per genotype-treatment combination were used as biological replicates. Because of the large number of analytical samples were grouped in 3 analytical batches for LC-MS analyses. Each batch contains 6 blocks of 10 analytical samples. The analytical samples were randomly assigned to batches and blocks within batches. Blanks were placed at the initial and final positions of each batch and QC samples were evenly distributed bordering blocks. QCs were balanced pools of the total sample extracts. Spectral data were acquired in a LC-ESI-QTOF mass spectrometer (Bruker Daltonics). MS acquisition was performed in both negative and positive ionization modes for full scan in a mass scan range of m/z 100-1200 with Bruker OTOF Control and DataAnalisys software (Bruker Daltonics).The dataset raw data were converted to mzML format with ProteoWizard MSConvert tool (Version: 3.0.24261). Biosynthesis of unsaturated fatty acids and linolenic acid metabolism were downregulated in susceptible inbreds under the FS treatment compared to CS treatment, and glutathione metabolism and aminoacyl-tRNA biosynthesis upregulated. Phenylalanine, tyrosine and tryptophan biosynthesis (PTTB) pathway was enriched in the comparison FS versus CS in resistant inbreds, as well as other pathways highly related with PTTB pathway such as isoquinoline alkaloid biosynthesis and ubiquinone and other-terpenoid-quinone biosynthesis pathways., This research was funded by subsequent coordinated projects financed by MCIU/AEI/FEDER, UE (RTI2018-096776-B-C21, RTI2018-096776-B-C22, PID2021-122196OB-C21 and PID2021-122196OB-C22)., File List: MS NEG Batch 1.zip MS NEG Batch 2.zip MS NEG Batch 3.zip MS POS Batch 1.zip.001 MS POS Batch 1.zip.002 MS POS Batch 1.zip.003 MS POS Batch 2.zip.001 MS POS Batch 2.zip.002 MS POS Batch 3.zip.001 MS POS Batch 3.zip.002, Peer reviewed