Structure-related bandgap of hybrid lead halide perovskites and close-packed APbX3 family of phases

Metal halide perovskites APbX3 (A+ = FA+ (formamidinium), MA+ (methylammonium) or Cs+, X- = I-, Br-) are considered as prominent innovative components in nowadays perovskite solar cells. Crystallization of these materials is often complicated by the formation of various phases with the same stoichiometry but structural types deviating from perovskites such as well-known the hexagonal delta FAPbI3 polytype. Such phases are rarely placed in the focus of device engineering due to their unattractive optoelectronic properties while they are, indeed, highly important because they influence on the optoelectronic properties and efficiency of final devices. However, the total number of such phases has not been yet discovered and the complete configurational space of the polytypes and their band structures have not been studied systematically. In this work, we predicted and described all possible hexagonal polytypes of hybrid lead halides with the APbI3 composition using the group theory approach, also we analyzed theoretically the relationship between the configuration of close-packed layers in polytypes and their band gap using DFT calculations. Two main factors affecting the bandgap were found including the ratio of cubic (c) and hexagonal (h) close-packed layers and the thickness of blocks of cubic layers in the structures. We also show that the dependence of the band gap on the ratio of cubic (c) and hexagonal (h) layers in these structures are non-linear. We believe that the presence of such polytypes in the perovskite matrix might be a reason for a decrease in the charge carrier mobility and therefore it would be an obstacle for efficient charge transport causing negative consequences for the efficiency of solar cell devices

Supernova search with active learning in ZTF DR3

We provide the first results from the complete SNAD adaptive learning pipeline in the context of a broad scope of data from large-scale astronomical surveys. The main goal of this work is to explore the potential of adaptive learning techniques in application to big data sets. Our SNAD team used Active Anomaly Discovery (AAD) as a tool to search for new supernova (SN) candidates in the photometric data from the first 9.4 months of the Zwicky Transient Facility (ZTF) survey, namely, between March 17 and December 31 2018 (58194 < MJD < 58483). We analysed 70 ZTF fields at a high galactic latitude and visually inspected 2100 outliers. This resulted in 104 SN-like objects being found, 57 of which were reported to the Transient Name Server for the first time and with 47 having previously been mentioned in other catalogues, either as SNe with known types or as SN candidates. We visually inspected the multi-colour light curves of the non-catalogued transients and performed fittings with different supernova models to assign it to a probable photometric class: Ia, Ib/c, IIP, IIL, or IIn. Moreover, we also identified unreported slow-evolving transients that are good superluminous SN candidates, along with a few other non-catalogued objects, such as red dwarf flares and active galactic nuclei. Beyond confirming the effectiveness of human-machine integration underlying the AAD strategy, our results shed light on potential leaks in currently available pipelines. These findings can help avoid similar losses in future large-scale astronomical surveys. Furthermore, the algorithm enables direct searches of any type of data and based on any definition of an anomaly set by the expert.Comment: 22 pages with appendix, 12 figures, 2 tables, accepted for publication in Astronomy and Astrophysic

Fast Neural Network Engine for Natural Science Language Processing: A Drug-Search Case.

The main advantage of modern natural language processing methods is a possibility to turn an amorphous human-readable task into a strict mathematic form. That allows to extract chemical data and insights from articles and to find new semantic relations. We propose a universal engine for processing chemical and biological texts. We successfully tested it on various use-cases and applied to a case of searching a therapeutic agent for a COVID-19 disease by analyzing PubMed archive

Comparing Five and Lower-Dimensional Grain Boundary Character and Energy Distributions in Copper : Experiment and Molecular Statics Simulation

The misorientation of 515 grain boundaries has been determined using electron backscatter diffraction data from an 18 μm thick copper foil with columnar grain structure and a preferential {110} surface orientation. The energy of the grain boundaries was determined from the dihedral angles in the vicinity of grain boundary thermal grooves. The experimental grain boundary energy vs. misorientation angle shows deep minima for the low-angle grain boundaries and small minima corresponding to the Σ3 and Σ9 grain boundaries. Only a small fraction of the coincidence site lattice grain boundaries demonstrate an increased occurrence frequency (compared to a random orientation distribution) and low energy. In parallel, the grain boundary energy for a subset of 400 symmetrical tilt grain boundaries was calculated using molecular statics simulations. There is a good agreement between the experiment and molecular statics modeling

Aroma Molecules as Dynamic Volatile Surfactants: Functionality Beyond the Scent

Understanding of non-equilibrium processes at dynamic interfaces is indispensable for advancing design and fabrication of solid state and soft materials.The research presented here unveils specific interfacial behavior of aroma molecules and justifies their usage as multifunctional volatile surfactants. As non-conventional volatile amphiphiles we study commercially available poorly water-soluble compounds from the classes of synthetic and essential flavor oils. Their distinctive feature is high dynamic interfacial activity, so that they decrease the surface tension of aqueous solutions on a time scale of milliseconds. Another potentially useful property of such amphiphiles is their volatility, so that they notably evaporate from interfaces on a time scale of seconds. This behavior allows for control of wetting and spreading processes. A revealed synergetic interfacial behavior of mixtures of conventional and volatile surfactants is attributed to a decrease of the adsorption barrier as a result of high statistical availability of new sites at the surface upon evaporation of the volatile component. Our results offer promising advantages in manufacturing technologies which involve newly creating interfaces, such as spraying, coating technologies, ink-jet printing, microfluidics, laundry, stabilization of emulsions in cosmetic and food industry, as well as in geosciences for controlling aerosols formation

In Silico, In Vitro, and Clinical Investigations of Cathepsin B and Stefin A mRNA Expression and a Correlation Analysis in Kidney Cancer

The cysteine protease Cathepsin B (CtsB) plays a critical role in multiple signaling pathways, intracellular protein degradation, and processing. Endogenous inhibitors regulate its enzymatic activity, including stefins and other cystatins. Recent data proved that CtsB is implicated in tumor extracellular matrix remodeling, cell invasion, and metastasis: a misbalance between cathepsins and their natural inhibitors is often considered a sign of disease progression. In the present study, we investigated CtsB and stefin A (StfA) expression in renal cell carcinoma (RCC). mRNA analysis unveiled a significant CTSB and STFA increase in RCC tissues compared to adjacent non-cancerogenic tissues and a higher CtsB expression in malignant tumors than in benign renal neoplasms. Further analysis highlighted a positive correlation between CtsB and StfA expression as a function of patient sex, age, tumor size, grade, lymph node invasion, metastasis occurrence, and survival. Alternative overexpression and silencing of CtsB and StfA confirmed the correlation expression between these proteins in human RCC-derived cells through protein analysis and fluorescent microscopy. Finally, the ectopic expression of CtsB and StfA increased RCC cell proliferation. Our data strongly indicated that CtsB and StfA expression play an important role in RCC development by mutually stimulating their expression in RCC progression