The development of technology for production of zeolites from fly-ash from Troitskaya power plant

The study examines the technology of processing fly ash from Troitskaya power plant for the production of zeolite. The paper presents the results of laboratory studies evaluating the suitability of fly ash from Troitskaya power plant for the production of zeolites and the development of the zeolite production process. Fly ash contains a small amount of heavy metals that can complicate processing, but contains a large amount of silicon oxide. The technology consists of high-temperature alkaline activation of fly ash and hydrochemical synthesis. The resulting powder has a specific surface area of 89.7 m2/g, determined by the BET method, and an average pore diameter of 0.345 μm. The static exchange capacity was 220 mg/g

Using the mineral component of building refuse in heavy metals sorption from their mixture

The sorption properties of the sand-breakstone mixture based on the mineral component of building refuse of the 0-10 mm fraction with respect to Pb2+, Zn2+, Cu2+, Ni2+, Cd2+ and Hg2+ ions were studied using atomic absorption spectroscopy. The mechanisms of accumulation of heavy metal ions on the surface of the mixture particles are described. It was found that after washing the contaminated material distilled water, the residual concentration of metals in the filtrate does not exceed the established sanitary and hygienic standards. The practical value of the work lies in the possibility of applying the results in reclamation of technogenic formations or production of materials for the technical stage of reclamation using technogenic soils

Thermodynamic Estimation of the Effect of Halcogenizer and Ligand on the Chemical Deposition of PbSe Films

The work was financially supported by program 211 of the Government of the Russian Federation (No. 02.A03.21.0006.

Bispyrenylalkane Chemosensor for the Naked-eye Detection of Nitro-explosives

Pyrene-based compounds have a great potential as fluorescent chemosensors for various analytes including common nitro-explosives, such as 2,4,6-trinitrotoluene (TNT). Compounds having two pyrene units in one molecule, such as bispyrenylalkanes, are able to form stable, bright emissive in a visual wavelength region excimers both in non-polar and polar environments. In this work we wish to report that in non-polar solvents the excimer has poor chemosensing properties while in aqueous solutions it provides significant “turn-off” fluorescence response to TNT in the sub-nanomolar concentrations

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

PROSPECTS FOR THE DEVELOPMENT OF THE INDUSTRY OF DEEP PROCESSING OF POLYMER WASTE

The necessity of the development of technologies for the deep recycling of polymer waste are shown in the present work. Perspective trends in this research area are also suggested

Computer Visionvs.spectrofluorometer-Assisted Detection of Common Nitro-Explosive Components Withbola-Type PAH-Based Chemosensors

Computer vision (CV) algorithms are widely utilized in imaging processing for medical and personal electronics applications. In sensorics CV can provide a great potential to quantitate chemosensors' signals. Here we wish to describe a method for the CV-assisted spectrofluorometer-free detection of common nitro-explosive components,e.g.2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT), by using polyaromatic hydrocarbon (PAH, PAH = 1-pyrenyl or 9-anthracenyl) - basedbola-type chemosensors. The PAH components of these chemicalbolasare able to form stable, bright emissive in a visual wavelength region excimers, which allows their use as extended matrices of the RGB colors after imaging and digital processing. In non-polar solvents, the excimers have poor chemosensing properties, while in aqueous solutions, due to the possible micellar formation, these excimers provide “turn-off” fluorescence detection of DNT and TNT in the sub-nanomolar concentrations. A combination of these PAH-based fluorescent chemosensors with the proposed CV-assisted algorithm offers a fast and convenient approach for on-site, real-time, multi-thread analyte detection without the use of fluorometers. Although we focus on the analysis of nitro-explosives, the presented method is a conceptual work describing a general use of CV for quantitative fluorescence detection of various analytes as a simpler alternative to spectrofluorometer-assisted methods. © The Royal Society of Chemistry 2021.This work was supported by RFBR, project number 19-33-90155

Computer vision vs. spectrofluorometer-assisted detection of common nitro-explosive components with bola-type PAH-based chemosensors

Computer vision (CV) algorithms are widely utilized in imaging processing for medical and personal electronics applications. In sensorics CV can provide a great potential to quantitate chemosensors' signals. Here we wish to describe a method for the CV-assisted spectrofluorometer-free detection of common nitro-explosive components, e.g. 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT), by using polyaromatic hydrocarbon (PAH, PAH = 1-pyrenyl or 9-anthracenyl) – based bola-type chemosensors. The PAH components of these chemical bolas are able to form stable, bright emissive in a visual wavelength region excimers, which allows their use as extended matrices of the RGB colors after imaging and digital processing. In non-polar solvents, the excimers have poor chemosensing properties, while in aqueous solutions, due to the possible micellar formation, these excimers provide “turn-off” fluorescence detection of DNT and TNT in the sub-nanomolar concentrations. A combination of these PAH-based fluorescent chemosensors with the proposed CV-assisted algorithm offers a fast and convenient approach for on-site, real-time, multi-thread analyte detection without the use of fluorometers. Although we focus on the analysis of nitro-explosives, the presented method is a conceptual work describing a general use of CV for quantitative fluorescence detection of various analytes as a simpler alternative to spectrofluorometer-assisted methods