Spectral broadening in self-assembled GaAs quantum dots with narrow size distribution

The control over the spectral broadening of an ensemble of emitters, mainly attributable to the size and shape dispersion and the homogenous broadening mechanisms, is crucial to several applications of quantum dots. We present a convenient self-assembly approach to deliver strain-free GaAs quantum dots with size distribution below 15%, due to the control of the growth parameters during the preliminary formation of the Ga droplets. This results in an ensemble photoluminescence linewidth of 19 meV at 14 K. The narrow emission band and the absence of a wetting layer promoting dot-dot coupling allow us to deconvolve the contribution of phonon broadening in the ensemble photoluminescence and study it in a wide temperature range.Comment: 9 pages, 4 figure

Optically controlled dual-band quantum dot infrared photodetector

We present the design for a novel type of dual-band photodetector in the thermal infrared spectral range, the Optically Controlled Dual-band quantum dot Infrared Photodetector (OCDIP). This concept is based on a quantum dot ensemble with a unimodal size distribution, whose absorption spectrum can be controlled by optically-injected carriers. An external pumping laser varies the electron density in the QDs, permitting to control the available electronic transitions and thus the absorption spectrum. We grew a test sample which we studied by AFM and photoluminescence. Based on the experimental data, we simulated the infrared absorption spectrum of the sample, which showed two absorption bands at 5.85 um and 8.98 um depending on the excitation power

Characterization of nitrogen dioxide variability using ground-based and satellite remote sensing and in situ measurements in the Tiber valley (Lazio, Italy)

The spatial-temporal distributions of nitrogen dioxide (NO2) in a rural area of Tiber valley were evaluated over one year (March 2022-February 2023) using remote sensing and in situ measurements. Surface concentration monitoring was conducted using a Pandora-2s spectrometer and a chemiluminescence analyzer operated at the Liberti Observatory (CNR-IIA). In spring, when the growing season and the agricultural activities increase, NO2 peaks were detectable by the Pandora but not by the in situ analyzer. The tropospheric Pandora and TROPOMI VCD products showed similar temporal patterns as those of the analyzer at the Observatory. High TROPOMI VCD levels in spring were detected at the Observatory and at six sites selected as representative of rural, residential, and industrial environments. WRF simulations found that high pollution events, observed by the Pandora and analyzer, occurred in calm wind conditions, favouring the accumulation of NO2 locally emitted. The complementary dataset provided by remote sensing and in situ techniques efficiently captured the spatial-temporal NO2 variability in a rural site exposed to low emission sources, thus supporting future decisional policies and actions

Enhancing intermediate band solar cell performances through quantum engineering of dot states by droplet epitaxy

We report the effect of the quantum dot aspect ratio on the sub-gap absorption properties of GaAs/AlGaAs quantum dot intermediate band solar cells. We have grown AlGaAs solar cells containing GaAs quantum dots made by droplet epitaxy. This technique allows the realization of strain-free nanostructures with lattice matched materials, enabling the possibility to tune the size, shape, and aspect ratio to engineer the optical and electrical properties of devices. Intermediate band solar cells have been grown with different dot aspect ratio, thus tuning the energy levels of the intermediate band. Here, we show how it is possible to tune the sub-gap absorption spectrum and the extraction of charge carriers from the intermediate band states by simply changing the aspect ratio of the dots. The tradeoff between thermal and optical extraction is in fact fundamental for the correct functioning of the intermediate band solar cells. The combination of the two effects makes the photonic extraction mechanism from the quantum dots increasingly dominant at room temperature, allowing for a reduction of the open circuit voltage of only 14 mV, compared to the reference cell.publishedVersionPeer reviewe

GaAs epilayers grown on patterned (001) silicon substrates via suspended Ge layers

We demonstrate the growth of low density anti-phase boundaries, crack-free GaAs epilayers, by Molecular Beam Epitaxy on silicon (001) substrates. The method relies on the deposition of thick GaAs on a suspended Ge buffer realized on top of deeply patterned Si substrates by means of a three-temperature procedure for the growth. This approach allows to suppress, at the same time, both threading dislocations and thermal strain in the epilayer and to remove anti-phase boundaries even in absence of substrate tilt. Photoluminescence measurements show the good uniformity and the high optical quality of AlGaAs/GaAs quantum well structures realized on top of such GaAs layer

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

Carriers of ADAMTS13 Rare Variants Are at High Risk of Life-Threatening COVID-19

Thrombosis of small and large vessels is reported as a key player in COVID-19 severity. However, host genetic determinants of this susceptibility are still unclear. Congenital Thrombotic Thrombocytopenic Purpura is a severe autosomal recessive disorder characterized by uncleaved ultra-large vWF and thrombotic microangiopathy, frequently triggered by infections. Carriers are reported to be asymptomatic. Exome analysis of about 3000 SARS-CoV-2 infected subjects of different severities, belonging to the GEN-COVID cohort, revealed the specific role of vWF cleaving enzyme ADAMTS13 (A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 13). We report here that ultra-rare variants in a heterozygous state lead to a rare form of COVID-19 characterized by hyper-inflammation signs, which segregates in families as an autosomal dominant disorder conditioned by SARS-CoV-2 infection, sex, and age. This has clinical relevance due to the availability of drugs such as Caplacizumab, which inhibits vWF-platelet interaction, and Crizanlizumab, which, by inhibiting P-selectin binding to its ligands, prevents leukocyte recruitment and platelet aggregation at the site of vascular damage