Environmental STEM Study of the Oxidation Mechanism for Iron and Iron Carbide Nanoparticles

The oxidation of solution-synthesized iron (Fe) and iron carbide (Fe2C) nanoparticles was studied in an environmental scanning transmission electron microscope (ESTEM) at elevated temperatures under oxygen gas. The nanoparticles studied had a native oxide shell present, that formed after synthesis, an ~3 nm iron oxide (FexOy) shell for the Fe nanoparticles and ~2 nm for the Fe2C nanoparticles, with small void areas seen in several places between the core and shell for the Fe and an ~0.8 nm space between the core and shell for the Fe2C. The iron nanoparticles oxidized asymmetrically, with voids on the borders between the Fe core and FexOy shell increasing in size until the void coalesced, and finally the Fe core disappeared. In comparison, the oxidation of the Fe2C progressed symmetrically, with the core shrinking in the center and the outer oxide shell growing until the iron carbide had fully disappeared. Small bridges of iron oxide formed during oxidation, indicating that the Fe transitioned to the oxide shell surface across the channels, while leaving the carbon behind in the hollow core. The carbon in the carbide is hypothesized to suppress the formation of larger crystallites of iron oxide during oxidation, and alter the diffusion rates of the Fe and O during the reaction, which explains the lower sensitivity to oxidation of the Fe2C nanoparticles

Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology

Catalysing sustainable fuel and chemical synthesis

Concerns over the economics of proven fossil fuel reserves, in concert with government and public acceptance of the anthropogenic origin of rising CO2 emissions and associated climate change from such combustible carbon, are driving academic and commercial research into new sustainable routes to fuel and chemicals. The quest for such sustainable resources to meet the demands of a rapidly rising global population represents one of this century’s grand challenges. Here, we discuss catalytic solutions to the clean synthesis of biodiesel, the most readily implemented and low cost, alternative source of transportation fuels, and oxygenated organic molecules for the manufacture of fine and speciality chemicals to meet future societal demands