A Density Functional Theory Study of Raman Modes of Hydrogenated Cadmium Sulphide Nanoparticles

Raman scattering investigations based on density functional theory (DFT) calculations were performed to explore the vibrational modes of wurtzite structured CdS nanoparticles (NPs). The calculations were performed to obtain the Raman spectra for the CdS containing 2, 4, 8 and 12 atoms to study the size dependence. Several vibrational modes indicating stretching and bending features related to Cd and S atoms were observed. Modifications of the frequency and intensity of different Raman modes with an increase in number of atoms in NPs are discussed in detail. It is found that the frequency of the CdS symmetric stretching mode of vibration shows a consistent red shift and that of CdS anti‐symmetric stretching shows a consistent blue shift with the increase in the number of atoms. Hydrogen atoms were added in order to make the closed shell configuration and saturate the NPs as per the requisite for calculating the Raman spectra. This produced some additional modes of vibration related to hydrogen atoms. The SH stretching mode showed a consistent red shift and the CdH stretching mode showed a consistent blue shift with an increase in the number of atoms in NPs. The results generated are found to be in close agreement with the literature. The observed red shift in different modes is assigned to stimulated Raman stretching and blue shift is ascribed to the coherent anti‐stokes Raman scattering

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Optimal Icosahedral Copper-Based Bimetallic Clusters for the Selective Electrocatalytic CO2 Conversion to One Carbon Products

Electrochemical CO2 reduction reactions can lead to high value-added chemical and materials production while helping decrease anthropogenic CO2 emissions. Copper metal clusters can reduce CO2 to more than thirty different hydrocarbons and oxygenates yet they lack the required selectivity. We present a computational characterization of the role of nano-structuring and alloying in Cu-based catalysts on the activity and selectivity of CO2 reduction to generate the following one-carbon products: carbon monoxide (CO), formic acid (HCOOH), formaldehyde (H2C=O), methanol (CH3OH) and methane (CH4). The structures and energetics were determined for the adsorption, activation, and conversion of CO2 on monometallic and bimetallic (decorated and core@shell) 55-atom Cu-based clusters. The dopant metals considered were Ag, Cd, Pd, Pt, and Zn, located at different coordination sites. The relative binding strength of the intermediates were used to identify the optimal catalyst for the selective CO2 conversion to one-carbon products. It was discovered that single atom Cd or Zn doping is optimal for the conversion of CO2 to CO. The core@shell models with Ag, Pd and Pt provided higher selectivity for formic acid and formaldehyde. The Cu-Pt and Cu-Pd showed lowest overpotential for methane formation

Experimental and Theoretical Investigation of Ferromagnetism in Mn-Doped SnO

In this paper, Mn doped SnO nanomaterial is studied both experimentally and theoretically. Hexagonal-shaped Mn-doped SnO nanostructures are successfully synthesized by the simple template-free hydrothermal method. All theoretical results are calculated using ADF-BAND 2012.01. The experimental and the theoretical results prove the ferromagnetism of Mn doped SnO. The morphology, crystalline phase, particle sizes and atomic weight percentage of atoms are investigated by X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), and energy-dispersive X-ray spectroscopy (EDS), respectively. FESEM results show that the sheets-like SnO structure are in the range of 10 mu m and the average size of nano-hexagonal plates is about 100 nm. The average crystalline size of the tetragonal phase SnO particles is calculated to be about 25 nm from XRD results. Two Raman active modes A(1g) = 205 cm(-1) and B-1g = 106 cm(-1) and about 7 cm(-1) redshift are observed by the Raman spectroscopy. The experimental results are consistent with theoretical results

Ab initio random structure searching and catalytic properties of copper-based nanocluster with Earth-abundant metals for the electrocatalytic CO2-to-CO conversion

Understanding the effect of nano-structuring and metal doping on the properties of copper-based clusters is crucial to developing effective catalysts for the electrochemical conversion of CO2 to value-added chemicals. We present a computational approach based on density functional and random structure searching to investigate the structures of mono- and bi-bimetallic nanoclusters, the acti-vation of CO2 on the catalyst, and the mechanism of CO2 dissociation. We have applied this approach to predict the structure and catalytic properties of Cun (n = 1–55) and (Cu-M)m (M = Fe, Sn, Zn with 1 ≤ m ≤ 27) nanoclusters. We also considered the CO2 acti-vation and conversion on the low index Cu and Cu-M (100) surfaces and high-symmetry (icosahedral) and core-shell Cu-M clusters. We found low-symmetry pure copper clusters with an amorphous character to be the most stable and have higher catalytic activity than the copper surface and high-symmetry icosahedral nanoclusters. In both pure copper and bimetallic systems, the physiosorbed state of CO2 is the most stable and energy is required to activate the molecule. Stabilization of the chemisorbed state occurs in sys-tems such as Cu-Fe where there is a delocalization of orbitals around the Fermi level, causing the large charge transfer from the cata-lyst to CO2. We have also conducted calculations of the free energy profiles of the CO2-to-CO conversion and the competitive hy-drogen evolution reaction (HER). The CO2 reduction reaction is dominant over HER on the Cu randomly generated cluster due to the lower potential limiting step. Among other considered bimetallic, the core@shell models also display good catalytic activity and selectivity towards the CO2 reduction reaction. This work identifies insightful structure-property relationships for CO2 activation, highlighting the influence of size and composition on the CO2 activation and intermediate stability in designing catalytic cupper-based mono- and bi-metallic clusters for the CO2 reduction reaction

Enhanced Photocatalytic Water Splitting with Two-Dimensional van der Waals Heterostructures of BAs/WTeSe

The photocatalytic efficiency of monolayer materials can be significantly enhanced by constructing two-dimensional van der Waals heterostructures. This study presents first principles calculations based on density functional theory to investigate the electronic properties and photocatalytic mechanism of van der Walls heterostructures of boron arsenide (BAs) with the Janus MXY (M=W; X/Y=Se, Te) monolayers, with and without Se vacancies. Results from binding energies, phonon spectra, and ab initio molecular dynamics simulations indicate that the heterostructures are stable from all respects. Moreover, all the heterostructures exhibit direct bandgaps with valence band maxima and conduction band minima suitable for water splitting. Additionally, these heterostructures possess high optical absorption coefficients in the visible and ultraviolet regions. In particular, our calculations predict BAs/WTeSe, with and without Se vacancies, as promising candidates for photocatalytic water splitting applications

Study on the structure vs activity of designed non-precious metal electrocatalysts for CO2 conversion

The rising level of carbon dioxide (CO2), mainly a consequence of human activities, it is leading to devastating consequences to our environment and has raised concerns to the public opinion. To face this issue, governments are working to reduce the level of CO2 emissions, whilst the scientific community is focusing to implement the electro-chemical conversion of the emitted CO2 (CO2RR) as source of added value chemicals. Due to the high stability of the CO2 molecule, to make its conversion practical, the process requires a suitable electro-catalyst. With the aim to understand the mechanism toward specific CO2RR product and thus increase selectivity, in this contribution, we have explored copper nanoparticles (Cu NPs), as one of the most promising catalyst for CO2 conversion, and investigated the reactivity as a function of selected experimental parameters. The results were rationalized via theoretical investigation, also discussed in the paper, to understand the mechanism behind their activity but, most importantly, to relate structure to selectivity. The Cu NPs, prepared via an unconventional sol-gel process, were shown to be pure, with homogeneous size and morphology, and were tested toward CO2RRs showing a total FE above 90%. The higher FE toward the production of C2H4 (up to 33% at an applied potential of -1.0 V) is one of the highest FE reported so far for Cu, without using expensive support. The final products were characterized using X-ray diffraction (XRD) and scanning electron microscopy (SEM)