Strain engineering in Ge/GeSn core/shell nanowires

Strain engineering in Sn-rich group IV semiconductors is a key enabling factor to exploit the direct band gap at mid-infrared wavelengths. Here, we investigate the effect of strain on the growth of GeSn alloys in a Ge/GeSn core/shell nanowire geometry. Incorporation of Sn content in the 10-20 at.% range is achieved with Ge core diameters ranging from 50nm to 100nm. While the smaller cores lead to the formation of a regular and homogeneous GeSn shell, larger cores lead to the formation of multi-faceted sidewalls and broadened segregation domains, inducing the nucleation of defects. This behavior is rationalized in terms of the different residual strain, as obtained by realistic finite element method simulations. The extended analysis of the strain relaxation as a function of core and shell sizes, in comparison with the conventional planar geometry, provides a deeper understanding of the role of strain in the epitaxy of metastable GeSn semiconductors

Morphological evolution via surface diffusion learned by convolutional, recurrent neural networks: extrapolation and prediction uncertainty

We use a Convolutional Recurrent Neural Network approach to learn morphological evolution driven by surface diffusion. To this aim we first produce a training set using phase field simulations. Intentionally, we insert in such a set only relatively simple, isolated shapes. After proper data augmentation, training and validation, the model is shown to correctly predict also the evolution of previously unobserved morphologies and to have learned the correct scaling of the evolution time with size. Importantly, we quantify prediction uncertainties based on a bootstrap-aggregation procedure. The latter proved to be fundamental in pointing out high uncertainties when applying the model to more complex initial conditions (e.g. leading to splitting of high aspect-ratio individual structures). Automatic smart-augmentation of the training set and design of a hybrid simulation method are discussed.Comment: 11 pages, 7 figure

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

Targeted degraders of eIF6: a novel strategy to remodulate liver pathological lipidic metabolism

Among the crucial mechanisms involved in gene expression, translational control has proved to play a pivotal role. eIF6, a translation initiation factor that operates downstream of the insulin pathway, has recently emerged as a potential drug target: mice heterozygous for this factor reduce the upregulation of protein synthesis under postprandial conditions and exhibit reduced white fat accumulation [1]. It is well-known that increased lipid accumulation in the liver leads to non-alcoholic fatty liver disease (NAFLD), which can progress to non-alcoholic steatohepatitis (NASH) and eventually to hepatocellular carcinoma (HCC), a leading cause of cancer-related death worldwide. Notably, fatty liver is the fastest-growing cause of liver failure and HCC. Recent studies have shown that genetic inhibition of eIF6 reduces lipid metabolism and impedes NAFLD to HCC progression [2]. Based on these studies, inhibiting eIF6 could represent an effective strategy to prevent the pathological development of NAFLD, its progression to NASH, and subsequently to HCC, as well as the progression of existing HCC. To test this hypothesis, we designed selective degraders of eIF6 based on the molecular skeleton of known eIF6 binders previously identified and applied the emerging “proteolysis targeting chimera” (PROTAC) strategy. Thus, an in silico study of a set of degraders of eIF6 was performed, combining docking, molecular dynamics simulations and ligand binding free energy (MM-GBSA) approaches. The top scoring candidates are currently under development: the design, synthesis and characterization of these novel, putative PROTACs will be presented and discussed

PCSK9 inhibitors: a patent review 2018-2023

Introduction Proprotein convertase subtilisin/kexin 9 (PCSK9) plays a crucial role in breaking down the hepatic low-density lipoprotein receptor (LDLR), thereby influencing the levels of circulating low-density lipoprotein cholesterol (LDL-C). Consequently, inhibiting PCSK9 through suitable ligands has been established as a validated therapeutic strategy for combating hypercholesterolemia and cardiovascular diseases. Area covered Patent literature claiming novel compounds inhibiting PCSK9 disclosed from 2018 to June 2023 available in the espacenet database, which contains more than 150 million patent documents from over 100 patent-granting authorities worldwide. Expert opinion The undisputable beneficial influence of PCSK9 as a pharmacological target has prompted numerous private and public institutions to patent chemical frameworks as inhibitors of PCSK9. While several compounds have advanced to clinical trials for treating hypercholesterolemia, they have not completed these trials yet. These compounds must contend in a complex market where new, costly, and advanced drugs, such as monoclonal antibodies and siRNA, are prescribed instead of inexpensive and less potent statins

Self-assembly of C60 on a ZnTPP/Fe(001)–p(1 × 1)O substrate: observation of a quasi-freestanding C60 monolayer

Fullerene (C(60)) has been deposited in ultrahigh vacuum on top of a zinc tetraphenylporphyrin (ZnTPP) monolayer self-assembled on a Fe(001)–p(1 × 1)O substrate. The nanoscale morphology and the electronic properties of the C(60)/ZnTPP/Fe(001)–p(1 × 1)O heterostructure have been investigated by scanning tunneling microscopy/spectroscopy and ultraviolet photoemission spectroscopy. C(60) nucleates compact and well-ordered hexagonal domains on top of the ZnTPP buffer layer, suggesting a high surface diffusivity of C(60) and a weak coupling between the overlayer and the substrate. Accordingly, work function measurements reveal a negligible charge transfer at the C(60)/ZnTPP interface. Finally, the difference between the energy of the lowest unoccupied molecular orbital (LUMO) and that of the highest occupied molecular orbital (HOMO) measured on C(60) is about 3.75 eV, a value remarkably higher than those found in fullerene films stabilized directly on metal surfaces. Our results unveil a model system that could be useful in applications in which a quasi-freestanding monolayer of C(60) interfaced with a metallic electrode is required

Kinetic Control of Morphology and Composition in Ge/GeSn Core/Shell Nanowires

The growth of Sn-rich group-IV semiconductors at the nanoscale provides new paths for understanding the fundamental properties of metastable GeSn alloys. Here, we demonstrate the effect of the growth conditions on the morphology and composition of Ge/GeSn core/shell nanowires by correlating the experimental observations with a theoretical interpretation based on a multi-scale approach. We show that the cross-sectional morphology of Ge/GeSn core/shell nanowires changes from hexagonal to dodecagonal upon increasing the supply of the Sn precursor. This transformation strongly influences the Sn distribution as a higher Sn content is measured under the {112} growth front. Ab-initio DFT calculations provide an atomic-scale explanation by showing that Sn incorporation is favored at the {112} surfaces, where the Ge bonds are tensile-strained. A phase-field continuum model was developed to reproduce the morphological transformation and the Sn distribution within the wire, shedding light on the complex growth mechanism and unveiling the relation between segregation and faceting. The tunability of the photoluminescence emission with the change in composition and morphology of the GeSn shell highlights the potential of the core/shell nanowire system for opto-electronic devices operating at mid-infrared wavelengths

Faceting of Si and Ge crystals grown on deeply patterned Si substrates in the kinetic regime: phase-field modelling and experiments

The development of three-dimensional architectures in semiconductor technology is paving the way to new device concepts for various applications, from quantum computing to single photon avalanche detectors. In most cases, such structures are achievable only under far-from-equilibrium growth conditions. Controlling the shape and morphology of the growing structures, to meet the strict requirements for an application, is far more complex than in close-to-equilibrium cases. The development of predictive simulation tools can be essential to guide the experiments. A versatile phase-field model for kinetic crystal growth is presented and applied to the prototypical case of Ge/Si vertical microcrystals grown on deeply patterned Si substrates. These structures, under development for innovative optoelectronic applications, are characterized by a complex three-dimensional set of facets essentially driven by facet competition. First, the parameters describing the kinetics on the surface of Si and Ge are fitted on a small set of experimental results. To this goal, Si vertical microcrystals have been grown, while for Ge the fitting parameters have been obtained from data from the literature. Once calibrated, the predictive capabilities of the model are demonstrated and exploited for investigating new pattern geometries and crystal morphologies, offering a guideline for the design of new 3D heterostructures. The reported methodology is intended to be a general approach for investigating faceted growth under far-from-equilibrium conditions