Computational prediction of L_{3} EXAFS spectra of gold nanoparticles from classical molecular dynamics simulations

We present a computational approach for the simulation of extended x-ray absorption fine structure (EXAFS) spectra of nanoparticles directly from molecular dynamics simulations without fitting any of the structural parameters of the nanoparticle to experimental data. The calculation consists of two stages. First, a molecular dynamics simulation of the nanoparticle is performed and then the EXAFS spectrum is computed from “snapshots” of structures extracted from the simulation. A probability distribution function approach calculated directly from the molecular dynamics simulations is used to ensure a balanced sampling of photoabsorbing atoms and their surrounding scattering atoms while keeping the number of EXAFS calculations that need to be performed to a manageable level. The average spectrum from all configurations and photoabsorbing atoms is computed as an Au L3-edge EXAFS spectrum with the FEFF 8.4 package, which includes the self-consistent calculation of atomic potentials. We validate and apply this approach in simulations of EXAFS spectra of gold nanoparticles with sizes between 20 and 60 Å. We investigate the effect of size, structural anisotropy, and thermal motion on the gold nanoparticle EXAFS spectra and we find that our simulations closely reproduce the experimentally determined spectra

Dominance of grain size impacts on seasonal snow albedo at deforested sites in New Hampshire

Snow cover serves as a major control on the surface energy budget in temperate regions due to its high reflectivity compared to underlying surfaces. Winter in the northeastern United States has changed over the last several decades, resulting in shallower snowpacks, fewer days of snow cover, and increasing precipitation falling as rain in the winter. As these climatic changes occur, it is imperative that we understand current controls on the evolution of seasonal snow albedo in the region. Over three winter seasons between 2013 and 2015, snow characterization measurements were made at three open sites across New Hampshire. These near-daily measurements include spectral albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density, black carbon content, local meteorological parameters, and analysis of storm trajectories using the Hybrid Single-Particle Lagrangian Integrated Trajectory model. Using analysis of variance, we determine that land-based winter storms result in marginally higher albedo than coastal storms or storms from the Atlantic Ocean. Through multiple regression analysis, we determine that snow grain size is significantly more important in albedo reduction than black carbon content or snow density. And finally, we present a parameterization of albedo based on days since snowfall and temperature that accounts for 52% of variance in albedo over all three sites and years. Our improved understanding of current controls on snow albedo in the region will allow for better assessment of potential response of seasonal snow albedo and snow cover to changing climate

Fitting EXAFS data using molecular dynamics outputs and a histogram approach

The estimation of metal nanoparticle diameter by analysis of extended x-ray absorption fine structure (EXAFS) data from coordination numbers is nontrivial, particularly for particles <5 nm in diameter, for which the undercoordination of surface atoms becomes an increasingly significant contribution to the average coordination number. These undercoordinated atoms have increased degrees of freedom over those within the core of the particle, which results in an increase in the degree of structural disorder with decreasing particle size. This increase in disorder, however, is not accounted for by the standard means of EXAFS analysis, where each coordination shell is fitted with a single bond length and disorder term. In addition, the surface atoms of nanoparticles have been observed to undergo a greater contraction than those in the core, further increasing the range of bond distances. Failure to account for this structural change results in an increased disorder being measured, and therefore, a lower apparent coordination number and corresponding particle size are found. Here, we employ molecular dynamics (MD) simulations for a range of nanoparticle sizes to determine each of the nearest neighbor bond lengths, which were then binned into a histogram to construct a radial distribution function (RDF). Each bin from the histogram was considered to be a single scattering path and subsequently used in fitting the EXAFS data obtained for a series of carbon-supported platinum nanoparticles. These MD-based fits are compared with those obtained using a standard fitting model using Artemis and the standard model with the inclusion of higher cumulants, which has previously been used to account for the non-Gaussian distribution of neighboring atoms around the absorber. The results from all three fitting methods were converted to particle sizes and compared with those obtained from transmission electron microscopy (TEM) and x-ray diffraction (XRD) measurements. We find that the use of molecular dynamics simulations resulted in an improved fit over both the standard and cumulant models, in terms of both quality of fit and correlation with the known average particle size

Comparison of the spinels Co3O4 and NiCo2O4 as bifunctional oxygen catalysts in alkaline media

Data from experiments with both rotating disc electrodes (RDEs) and gas diffusion electrodes (GDEs) are used to investigate the properties of the spinels, Co3O4 and NiCo2O4, as bifunctional oxygen electrocatalysts. Emphasis is placed on catalyst compositions and electrode structures free of carbon. Oxygen evolution and reduction occur at surfaces where the transition metals are in different oxidation states but the surface can be repeatedly cycled between these two states without significant change. It is shown that carbon-free, NiCo2O4 catalysed GDEs can be fabricated using structures based on stainless steel cloth or nickel foam. Those based on nickel foam can be cycled extensively and allow both O2 evolution and reduction at current densities up to 100 mA cm?2

Hidden costs: The ethics of cost-effectiveness analyses for health interventions in resource-limited settings

Cost-effectiveness analysis (CEA) is an increasingly appealing tool for evaluating and comparing health-related interventions in resource-limited settings. The goal is to inform decision-makers regarding the health benefits and associated costs of alternative interventions, helping guide allocation of limited resources by prioritizing interventions that offer the most health for the least money. Although only one component of a more complex decision-making process, CEAs influence the distribution of healthcare resources, directly influencing morbidity and mortality for the world’s most vulnerable populations. However, CEA-associated measures are frequently setting-specific valuations, and CEA outcomes may violate ethical principles of equity and distributive justice. We examine the assumptions and analytical tools used in CEAs that may conflict with societal values. We then evaluate contextual features unique to resource-limited settings, including the source of health-state utilities and disability weights; implications of CEA thresholds in light of economic uncertainty; and the role of external donors. Finally, we explore opportunities to help align interpretation of CEA outcomes with values and budgetary constraints in resource-limited settings. The ethical implications of CEAs in resource-limited settings are vast. It is imperative that CEA outcome summary measures and implementation thresholds adequately reflect societal values and ethical priorities in resource-limited settings

Voltammetric studies of the mechanism of the oxygen reduction in alkaline media at the spinels Co3O4and NiCo2O4

The mechanism of O2 reduction at the spinels, Co3O4 and NiCo2O4, in KOH electrolyte is probed using voltammetry at rotating disc and rotating ring-disc electrodes by examination of the rotation rate dependent limiting currents. The analysis shows that the products and mechanisms at the two spinels are quite different. At the cobalt spinel, a substantial amount of the 2e? reduction product, H2O2, is formed while at NiCo2O4 the 4e? reduction strongly predominates. In terms of both the overpotential for reduction and its limiting current density, the mixed spinel is a substantially better electrocatalyst. It is proposed that the differences arise from an enhanced rate of O-O bond cleavage early in the reduction process at NiCo2O4

A novel bifunctional oxygen GDE for alkaline secondary batteries

AbstractThis paper describes a novel procedure for the fabrication of a gas diffusion electrode (GDE) suitable for use as a bifunctional oxygen electrode in alkaline secondary batteries. The electrode is fabricated by pre-forming a PTFE-bonded nickel powder layer on a nickel foam substrate followed by deposition of NiCo2O4 spinel electrocatalyst by dip coating in a nitrate solution and thermal decomposition. The carbon-free composition avoids concerns over carbon corrosion at the potentials for oxygen evolution. The electrode shows acceptable overpotentials for both oxygen evolution and oxygen reduction at current densities up to 100mAcm−2. Stable performance during >100 successive, 1h oxygen reduction/evolution cycles at a current density of 20mAcm−2 in 8M NaOH at 333K was achieved

A novel bifunctional oxygen GDE for alkaline secondary batteries

This paper describes a novel procedure for the fabrication of a gas diffusion electrode (GDE) suitable for use as a bifunctional oxygen electrode in alkaline secondary batteries. The electrode is fabricated by pre-forming a PTFE-bonded nickel powder layer on a nickel foam substrate followed by deposition of NiCo2O4 spinel electrocatalyst by dip coating in a nitrate solution and thermal decomposition. The carbon-free composition avoids concerns over carbon corrosion at the potentials for oxygen evolution. The electrode shows acceptable overpotentials for both oxygen evolution and oxygen reduction at current densities up to 100 mA cm−2. Stable performance during >100 successive, 1 h oxygen reduction/evolution cycles at a current density of 20 mA cm−2 in 8 M NaOH at 333 K was achieved.European Commissio

Leucine Rich α-2 Glycoprotein: A Novel Neutrophil Granule Protein and Modulator of Myelopoiesis

Leucine-rich α2 glycoprotein (LRG1), a serum protein produced by hepatocytes, has been implicated in angiogenesis and tumor promotion. Our laboratory previously reported the expression of LRG1 in murine myeloid cell lines undergoing neutrophilic granulocyte differentiation. However, the presence of LRG1 in primary human neutrophils and a role for LRG1 in regulation of hematopoiesis have not been previously described. Here we show that LRG1 is packaged into the granule compartment of human neutrophils and secreted upon neutrophil activation to modulate the microenvironment. Using immunofluorescence microscopy and direct biochemical measurements, we demonstrate that LRG1 is present in the peroxidase-negative granules of human neutrophils. Exocytosis assays indicate that LRG1 is differentially glycosylated in neutrophils, and co-released with the secondary granule protein lactoferrin. Like LRG1 purified from human serum, LRG1 secreted from activated neutrophils also binds cytochrome c. We also show that LRG1 antagonizes the inhibitory effects of TGFβ1 on colony growth of human CD34+ cells and myeloid progenitors. Collectively, these data invoke an additional role for neutrophils in innate immunity that has not previously been reported, and suggest a novel mechanism whereby neutrophils may modulate the microenvironment via extracellular release of LRG1

Quality by design approach for early understanding of active pharmaceutical ingredient recovery process through dead-end filtration

This study applied some concepts of quality-by-design (QbD) approach for an early understanding of crystal recovery through filtration. A bespoke laboratory scale dead-end filtration platform (modified Biotage vacuum master (BVM) ≈ 50 mL working volume) was used to investigate the recovery of an active pharmaceutical ingredient (API) of different size distributions using acetaminophen crystals (micronised, medium-sized Bioxtra and coarse) as a case study. The method involved: (1) identification of critical process parameters (CPPs) with significant impact on process stability (a process risk evaluation step based on one factor at a time); (2) design of experiment to screen the influence of design factors (such as filter pore size, pressure difference, crystal loading and particle size distribution (PSD)) contributing to process instability based on process responses (volumetric flux and specific cake resistance); and (3) investigate the optimal process window for reduced probability of failure and process predictability. The filtration process responses were characterised by assessing the filtrate flow rate by the application of Darcy’s law. Initial assessments of process steadiness for acetaminophen crystals recovery shows that the filter pore size and API crystal sizes are critical. A non-linear process dependency was observed between the applied pressure difference, pore size, and crystal size. Screening crystal recovery conditions based on the design of experiment (DoE) approach indicated a steady filtration process for all crystal sizes tested except for coarse crystals which shows non-valid (negative) specific cake resistance at conditions of 5 µm pore size filter and 100 mbar pressure difference. However, pressure difference and pore size had a notable impact on the process responses. As a result, 10 µm pore size filter was used for investigating the optimal process window. Process predictability was demonstrated by data clustering and refinement based on partial least square model. The results showed good predictability with >98% regression between the predicted and experimental data. Verification of optimal operating window with less than 5% probability failure resulted in conditions of 300 – 450 mbar pressure difference and PSD of 45 – 110 µm. The approach studied using the small-scale BVM provided an early data gathering and systematic approach to understanding process interactions affecting crystal recovery through dead-end filtration