581 research outputs found
Correlative electrochemical microscopy of Li-Ion (De)intercalation at a series of individual LiMn2 O4 particles
The redox activity (Li‐ion intercalation/deintercalation) of a series of individual LiMn2O4 particles of known geometry and (nano)structure, within an array, is determined using a correlative electrochemical microscopy strategy. Cyclic voltammetry (current–voltage curve, I–E) and galvanostatic charge/discharge (voltage–time curve, E–t) are applied at the single particle level, using scanning electrochemical cell microscopy (SECCM), together with co‐location scanning electron microscopy that enables the corresponding particle size, morphology, crystallinity, and other factors to be visualized. This study identifies a wide spectrum of activity of nominally similar particles and highlights how subtle changes in particle form can greatly impact electrochemical properties. SECCM is well‐suited for assessing single particles and constitutes a combinatorial method that will enable the rational design and optimization of battery electrode materials
Scanning electrochemical cell microscopy : a versatile method for highly localised corrosion related measurements on metal surfaces
The development of tools that can probe corrosion related phenomena at the (sub)microscale is recognized to be increasingly important in order to understand the surface structural factors (grain orientation, inclusions etc.) that control the (electro)chemical stability (corrosion susceptibility, pitting, passivity etc.) of metal surfaces. Herein we consider the application of scanning electrochemical cell microscopy (SECCM), a relatively new member of the electrochemical droplet cell (EDC) family, for corrosion research and demonstrate the power of this technique for resolving structure and activity at the (sub)microscale. Hundreds of spatially-resolved (2 μm droplet size) potentiodynamic polarization experiments have been carried out on the several hours timescale and correlated to complementary structural information from electron backscatter diffraction (EBSD) and energy dispersive x-ray spectroscopy (EDS) in order to determine the effect of grain orientation and inclusions on electrochemical processes at low carbon steel in neutral solution (10 mM KNO3). Through this approach, it has been shown unequivocally that for the low index planes, anodic currents in the passive region (an indicator of corrosion susceptibility) are greatest on (101) planes compared to (100) and (111) planes. Furthermore, individual sub-micron MnS inclusions have been probed and shown to undergo active dissolution followed by rapid repassivation. This study demonstrates the high versatility of SECCM and the considerable potential of this technique for addressing structure-activity problems in corrosion and electromaterials science
Nanoscale electrochemical visualization of grain-dependent anodic iron dissolution from low carbon steel
The properties of steels and other alloys are often tailored to suit specific applications through the manipulation of microstructure (e.g., grain structure). Such microscopic heterogeneities are also known to modulate corrosion susceptibility/resistance, but the exact dependency remains unclear, largely due to the challenge of probing and correlating local electrochemistry and structure at complex (alloy) surfaces. Herein, high-resolution scanning electrochemical cell microscopy (SECCM) is employed to perform spatially-resolved potentiodynamic polarisation measurements, which, when correlated to co-located structural information from electron backscatter diffraction (EBSD), analytical scanning electron microscopy (SEM) and scanning transmission electron microscopy (STEM), reveal the relationship between anodic metal (iron) dissolution and the crystallographic orientation of low carbon steel in aqueous sulfuric acid (pH 2.3). Considering hundreds of individual measurements made on each of the low-index planes of body-centred cubic (bcc) low carbon steel, the rate of iron dissolution, and thus overall corrosion susceptibility, increases in the order (101) < (111) < (100). These results are rationalized by complementary density functional theory (DFT) calculations, where the experimental rate of iron dissolution correlates with the energy required to remove (and ionise) one iron atom at the surface of a lattice, calculated for each low index orientation. Overall, this study further demonstrates how nanometre-resolved electrochemical techniques such as SECCM can be effectively utilised to vastly improve the understanding of structure-function in corrosion science, particularly when combined with complementary, co-located structural characterisation (EBSD, STEM etc.) and computational analysis (DFT)
Surface microstructural controls on electrochemical hydrogen absorption at polycrystalline palladium
The ease by which hydrogen is absorbed into a metal can be either advantageous or deleterious, depending on the material and application in question. For instance, in metals such as palladium (Pd), rapid absorption kinetics are seen as a beneficial property for hydrogen purification and storage applications, whereas the contrary is true for structural metals such as steel, which are susceptible to mechanical degradation in a process known as hydrogen embrittlement. It follows that understanding how the microstructure of metals (i.e., grains and grain boundaries) influences adsorption and absorption kinetics would be extremely powerful to rationally design materials (e.g., alloys) with either a high affinity for hydrogen or resistance to hydrogen embrittlement. To this end, scanning electrochemical cell microscopy (SECCM) is deployed herein to study surface structure-dependent electrochemical hydrogen absorption across the surface of flame annealed polycrystalline Pd in aqueous sulfuric acid (considered the model system for the study of hydrogen absorption). Correlating spatially-resolved cyclic voltammetric data from SECCM with co-located structural information from electron backscatter diffraction (EBSD) reveals a clear relationship between the crystal orientation and the rate of hydrogen adsorption-absorption. Grains that are closest to the low-index orientations [i.e., the {100}, {101}, and {111} facets, face-centered cubic (fcc) system] facilitate the lowest rates of hydrogen absorption, whereas grains of high-index orientation (e.g., {411}) promoted higher rates. Apparently enhanced kinetics are also seen at grain boundaries, which is thought to arise from physical deformation of the Pd surface adjacent to the boundary, resulting from the flame annealing and quenching process. As voltammetric measurements are made across a wide potential range, these studies also reveal palladium oxide formation and stripping to be surface structure-dependent processes, and further highlight the power of combined SECCM-EBSD for structure-activity measurements in electrochemical science
Ability of SP12 mutant of S. typhi to effectively induce antibody responses to the mucosal antigen enterotoxigenic E. coli heat labile toxin B subunit after oral delivery to humans
We have evaluated an oral vaccine based on an Salmonella enteric serovar typhi (S. typhi) Ty2 derivative TSB7 harboring deletion mutations in ssaV (SPI-2) and aroC together with a chromosomally integrated copy of eltB encoding the B subunit of enterotoxigenic Escherichia coli heat labile toxin (LT-B) in volunteers. Two oral doses of 108 or 109 CFU were administered to two groups of volunteers and both doses were well tolerated, with no vaccinemia, and only transient stool shedding. Immune responses to LT-B and S. typhi lipopolysaccharide were demonstrated in 67 and 97% of subjects, respectively, without evidence of anti-carrier immunity preventing boosting of LT-B responses in many cases. Further development of this salmonella-based (spi-VEC) system for oral delivery of heterologous antigens appears warranted
Using Social Software for Teamwork and Collaborative Project Management in Higher Education
This paper discusses the potential role of social software in supporting teamwork and collaborative project management in higher education. Based on the fact that social software has been widely spread among young students nowadays, using it for collaborative learning is believed to increase students' involvement and create learning incentives. Two social software platforms, Graaasp and Google Wave are examined in terms of sustaining collaborative learning activities. Relevant existing features and possible extensions that enhance the learning experience are addressed. Benefits and challenges resulting from the bottom-up learning paradigm are also presented
Author Correction:The impact of sleep, physical activity and sedentary behaviour on symptoms of depression and anxiety before and during the COVID-19 pandemic in a sample of South African participants (Scientific reports (2021) 11 1 (24059))
NT-proBNP by Itself Predicts Death and Cardiovascular Events in High-Risk Patients With Type 2 Diabetes Mellitus
BACKGROUND: NT-proBNP (N-terminal pro-B-type natriuretic peptide) improves the discriminatory ability of risk-prediction
models in type 2 diabetes mellitus (T2DM) but is not yet used in clinical practice. We assessed the discriminatory strength of
NT-proBNP by itself for death and cardiovascular events in high-risk patients with T2DM.
METHODS AND RESULTS: Cox proportional hazards were used to create a base model formed by 20 variables. The discriminatory
ability of the base model was compared with that of NT-proBNP alone and with NT-proBNP added, using C-statistics. We studied 5509 patients (with complete data) of 8561 patients with T2DM and cardiovascular and/or chronic kidney disease who were
enrolled in the ALTITUDE (Aliskiren in Type 2 Diabetes Using Cardiorenal Endpoints) trial. During a median 2.6-year follow-up
period, 469 patients died and 768 had a cardiovascular composite outcome (cardiovascular death, resuscitated cardiac arrest,
nonfatal myocardial infarction, stroke, or heart failure hospitalization). NT-proBNP alone was as discriminatory as the base model
for predicting death (C-statistic, 0.745 versus 0.744, P=0.95) and the cardiovascular composite outcome (C-statistic, 0.723
versus 0.731, P=0.37). When NT-proBNP was added, it increased the predictive ability of the base model for death (C-statistic,
0.779 versus 0.744, P<0.001) and for cardiovascular composite outcome (C-statistic, 0.763 versus 0.731, P<0.001).
CONCLUSIONS: In high-risk patients with T2DM, NT-proBNP by itself demonstrated discriminatory ability similar to a multivariable model in predicting both death and cardiovascular events and should be considered for risk stratification.
REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00549757
MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models
Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEval/downloads
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