In situ FTIR spectroscopy studies on electrochemical redox processes of high nuclearity osmium carbonyl clusters

The electrochemical redox processes of two high nuclearity osmium carbonyl clusters [(PhP)N[OsC(CO) ]·PPN (1) and Os(CO) (6) have been studied by electrochemical in situ FTIR. The five oxidation states of 1, i.e., [OsC(CO)], have been characterized. There are no significant structural changes for these species. Hence, the ability of this decanuclear cluster to act as an electron reservoir has been demonstrated. The structural rearrangement associated with the two-electron reduction of bicapped tetrahedral 6 to octahedral dianion [Os(CO)] and [Os(CO)] tetraanion has also been investigated. © 1996 American Chemical Society.

Catalyst distribution and carbon nanotube morphology in multilayer forests by mixed CVD processes

Carbon nanotubes can be grown as forests of aligned fibers on a substrate with a catalyst coated prior to or added during synthesis. A major process interruption can initiate the growth of second and successive layers of forest on top or at the base of the existing layers which are thereby lifted up. We report on the generation of multilayer CNT forests where the first forest is generated either by catalyst coinjection (CCI) of ferrocene with hydrocarbon (xylene) or by catalyst predeposition (CPD) of iron followed with hydrocarbon (acetylene). Subsequent layers are then produced by CCI alone to give uniform (all CCI) or mixed (CPD and CCI) structures to study the distribution of the iron catalyst and CNT morphology and to determine whether the CPD forest templates or otherwise influences the growth of subsequent CCI forests. The bottom-up base growth of second and subsequent CCI forests is reaction rate controlled. CCI multilayer forests accumulate catalyst (iron) in a variety of distinct locations. A pre-existing CPD forest modifies subsequent CCI forest initiation, morphology, and catalyst distribution but does not itself accumulate catalyst or change appearance. © 2009 American Chemical Society.

Linking watershed terrain and hydrology to soil chemical properties, microbial communities and impacts on soil organic C in a humid mid-latitude forested watershed

Understanding the response of humid mid-latitude forests to changes in precipitation, temperature, nutrient cycling, and disturbance is critical to improving our predictive understanding of changes in the surface-subsurface energy balance due to climate change. Mechanistic understanding of the effects of long-term and transient moisture conditions are needed to quantify
linkages between changing redox conditions, microbial activity, and soil mineral and nutrient interactions on C cycling and greenhouse gas releases. To illuminate relationships between the soil chemistry, microbial communities and organic C we established transects across hydraulic and topographic gradients in a small watershed with transient moisture conditions. Valley bottoms tend to be more frequently saturated than ridge tops and side slopes which generally are only saturated when shallow storm flow zones are active. Fifty shallow (~36”) soil cores were collected during timeframes representative of low CO2, soil winter conditions and high CO2, soil summer conditions. Cores were subdivided into 240 samples based on pedology and analyses of the geochemical (moisture content, metals, pH, Fe species, N, C, CEC, AEC) and microbial (16S rRNA gene
amplification with Illumina MiSeq sequencing) characteristics were conducted and correlated to watershed terrain and hydrology. To associate microbial metabolic activity with greenhouse gas emissions we installed 17 soil gas probes, collected gas samples for 16 months and analyzed them for CO2 and other fixed and greenhouse gasses. Parallel to the experimental efforts our data is being used to support hydrobiogeochemical process modeling by coupling the Community Land Model (CLM) with a subsurface process model (PFLOTRAN) to simulate processes and interactions from the molecular to watershed scales. Including above ground processes (biogeophysics, hydrology, and vegetation dynamics), CLM provides mechanistic water, energy, and organic matter inputs to the surface/subsurface models, in which coupled biogeochemical reaction
networks are used to improve the representation of below-ground processes. Preliminary results suggest that inclusion of above ground processes from CLM greatly improves the prediction of moisture response and water cycle at the watershed scale.

A dynamic sampling methodology for plasma etch processes using Gaussian process regression

Plasma etch is a key process in modern semiconductor manufacturing facilities as it offers process simplification and yet greater dimensional tolerances compared to wet chemical etch technology. The main challenge of operating plasma etchers is to maintain a consistent etch rate spatially and temporally for a given wafer and for successive wafers processed in the same etch tool. Etch rate measurements require expensive metrology steps and therefore in general only limited sampling is performed. Furthermore, the results of measurements are not accessible in real-time, limiting the options for run-to-run control. This paper investigates a Virtual Metrology (VM) enabled Dynamic Sampling (DS) methodology as an alternative paradigm for balancing the need to reduce costly metrology with the need to measure more frequently and in a timely fashion to enable wafer-to-wafer control. Using a Gaussian Process Regression (GPR) VM model for etch rate estimation of a plasma etch process, the proposed dynamic sampling methodology is demonstrated and evaluated for a number of different predictive dynamic sampling rules. © 2013 IEEE.

Removal of microorganisms and their chemical metabolites from water using semiconductor photocatalysis

Semiconductor photocatalysis has been applied to the remediation of an extensive range of chemical pollutants in water over the past 30 years. The application of this versatile technology for removal of micro-organisms and cyanotoxins has recently become an area that has also been the subject of extensive research particularly over the past decade. This paper considers recent research in the application of semiconductor photocatalysis for the treatment of water contaminated with pathogenic micro-organisms and cyanotoxins. The basic processes involved in photocatalysis are described and examples of recent research into the use of photocatalysis for the removal of a range of microorganisms are detailed. The paper concludes with a review of the key research on the application of this process for the removal of chemical metabolites generated from cyanobacteria.

Control of biofilm growth through photodynamic treatments combined with chemical inhibitors: in vitro evaluation methods

The rock/atmosphere interface is inhabited by a complex microbial community including bacteria, algae and fungi. These communities are prominent biodeterioration agents and remarkably influence the status of stone monuments and buildings. Deeper comprehension of natural biodeterioration processes on stone surfaces has brought about a concept of complex microbial communities referred to as "subaerial biofilms". The practical implications of biofilm formation are that control strategies must be devised both for testing the susceptibility of the organisms within the biofilm and treating the established biofilm. Model multi-species biofilms associated with mineral surfaces that are frequently refractory to conventional treatment have been used as test targets. A combination of scanning microscopy with image analysis was applied along with traditional cultivation methods and fluorescent activity stains. Such a polyphasic approach allowed a comprehensive quantitative evaluation of the biofilm status and development. Effective treatment strategies incorporating chemical and physical agents have been demonstrated to prevent biofilm growth in vitro. Model biofilm growth on inorganic support was significantly reduced by a combination of PDT and biocides

Physico-chemical treatment methods for the removal of microcystins (cyanobacterial hepatotoxins) from potable waters

The incidence of cyanobacterial blooms in freshwaters, including drinking water reservoirs, has increased over the past few decades due to rising nutrient levels. Microcystins are hepatotoxins released from cyanobacteria and have been responsible for the death of humans as well as domestic and wild animals. Microcystins are chemically very stable and many processes have only limited efficacy in removing them. In this paper we review a range of water treatment methods which have been applied to removing microcystins from potable waters.

Does chemical composition of individual Scots pine trees determine the biodiversity of their associated ground vegetation?

Despite plant secondary metabolites being major determinants of species interactions and ecosystem processes, their role in the maintenance of biodiversity has received little attention. In order to investigate the relationship between chemical and biological diversity in a natural ecosystem, we considered the impact of chemical diversity in individual Scots pine trees (Pinus sylvestris) on species richness of associated ground vegetation. Scots pine trees show substantial genetically determined constitutive variation between individuals in concentrations of a group of secondary metabolites, the monoterpenes. When the monoterpenes of particular trees were assessed individually, there was no relationship with species richness of associated ground flora. However, the chemical diversity of monoterpenes of individual trees was significantly positively associated with the species richness of the ground vegetation beneath each tree, mainly the result of an effect among the non-woody vascular plants. This correlation suggests that the chemical diversity of the ecosystem dominant species has an important role in shaping the biodiversity of the associated plant community. The extent and significance of this effect, and its underlying processes require further investigation.

Theoretical Investigation of NH3-SCR Processes over Zeolites: A Review

The selective catalytic reduction (SCR) of NOx compounds with NH3 is a hot topic in recent years. Among various catalysts, zeolites are proved to be efficient and promising for NH3-SCR, yet the whole processes and intrinsic mechanism are still not well understood due to the structural complexity of zeolites. With the improvement of theoretical chemistry techniques, quantum-chemical calculations are now capable of modeling the structure, acidity, adsorption, and ultimately reaction pathways over zeolites to some extent. In this review, a brief summary of relevant concepts of NH3-SCR is presented. Cluster approaches, embedded techniques, and periodic treatments are described as three main methods. Details of quantum-chemical investigations toward the key issues such as, the structure of active sites, the adsorption of small molecules, and the reaction mechanism of NH3-SCR over zeolites are discussed. Finally, a perspective for future theoretical research is given. 

Complete framework for efficient characterisation of non-Markovian processes

A non-Markovian process is one that retains `memory' of its past. A systematic understanding of these processes is necessary to fully describe and harness a vast range of complex phenomena; however, no such general characterisation currently exists. This long-standing problem has hindered advances in understanding physical, chemical and biological processes, where often dubious theoretical assumptions are made to render a dynamical description tractable. Moreover, the methods currently available to treat non-Markovian quantum dynamics are plagued with unphysical results, like non-positive dynamics. Here we develop an operational framework to characterise arbitrary non-Markovian quantum processes. We demonstrate the universality of our framework and how the characterisation can be rendered efficient, before formulating a necessary and sufficient condition for quantum Markov processes. Finally, we stress how our framework enables the actual systematic analysis of non-Markovian processes, the understanding of their typicality, and the development of new master equations for the effective description of memory-bearing open-system evolution.