Luminescent ionogels based on europium-doped ionic liquids confined within silica-derived networks

Luminescent ionogels were prepared by doping an europium( III) tetrakis beta-diketonate complex into an imidazolium ionic liquid, followed by immobilization of the ionic liquid by confinement in a silica network. The ionogels were obtained by a non-hydrolytic method as perfect monoliths featuring both the transparency of silica and the ionic conductivity performances of ionic liquids. The ionogels contain 80 vol % of ionic liquid. The organic-inorganic hybrid materials showed a very intense red photoluminescence under ultraviolet irradiation. The red emission has a very high coloric purity.

Physicochemical and drug diffusion analysis of rifampicin containing polyethylene glycol-poly(epsilon-caprolactone) networks designed for medical device applications

This study reports the physicochemical and drug diffusion properties of rifampicin containing poly(epsilon-caprolactone) (PCL)/polyethylene glycol (PEG) networks, designed as bioactive biomaterials. Uniquely, the effects of the states of both rifampicin and PEG and the interplay between these components on these properties are described. PCL matrices containing rifampicin (1-5%, w/w) and PEG 200 (0-15%, w/w) were prepared by casting from an organic solvent (dichloromethane). The films were subsequently characterized in terms of their thermal/thermorheological, surface and tensile properties, biodegradation and drug diffusion/release properties. Incorporation of PEG and/or rifampicin significantly affected the tensile and surface properties of PCL, lowering the ultimate tensile strength, % elongation at break, Young modulus and storage and loss moduli. Both in the absence and presence of PEG, solubilisation of rifampicin within the crystalline domains of PCL was observed. PEG was present as a dispersed liquid phase. The release of rifampicin (3% loading) was unaffected by the presence of PEG. Similarly the release of rifampicin (5%) was unaffected by low concentrations of PEG (5-10%) however, at higher loadings, the release rate of rifampicin was enhanced by the presence of PEG. Rifampicin release (10% loading) was enhanced by the presence of PEG in a concentration dependent fashion. These observations were accredited to enhanced porosity of the matrix. In all cases, diffusion-controlled release of rifampicin occurred which was unaffected by polymer degradation. This study has uniquely illustrated the effect of hydrophilic pore formers on the physicochemical properties of PCL. Interestingly, enhanced diffusion controlled release was only observed from biomaterials containing high loadings of PEG and rifampicin (5, 10%), concentrations that were shown to affect the mechanical properties of the biomaterials. Care should therefore be shown when adopting this strategy to enhance release of bioactive agents from biomaterials. (C) 2011 Elsevier B.V. All rights reserved.

Predicting organic acid concentration from UV/vis spectrometry measurements - A comparison of machine learning techniques

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

Nanoporous metal organic framework materials for hydrogen storage

Hydrogen is expected to play an important role in future transportation as a promising alternative clean energy source to carbon-based fuels. One of the key challenges to commercialize hydrogen energy is to develop appropriate onboard hydrogen storage systems, capable of charging and discharging large quantities of hydrogen with fast enough kinetics to meet commercial requirements. Metal organic framework (MOF) is a new type of inorganic and organic hybrid nanoporous particulate materials. Its diverse networks can enhance hydrogen storage through tuning the structure and property of MOFs. The MOF materials so far developed adsorb hydrogen through weak dispersion interactions, which allow significant quantity of hydrogen to be stored at cryogenic temperatures with fast kinetics. Novel MOFs are being developed to strengthen the interactions between hydrogen and MOFs in order to store hydrogen under ambient conditions. This review surveys the development of such candidate materials, their performance and future research needs. (C) 2009 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

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.

Metabolism of mineral-sorbed organic matter depends upon microbial lifestyle in fluvial ecosystems

In fluvial ecosystems mineral erosion, carbon (C) and nitrogen (N) fluxes are linked via organo-mineral complexation, where dissolved organic molecules bind to mineral surfaces. Biofilms and suspended aggregates represent major aquatic microbial lifestyles whose relative importance changes predictably through fluvial networks. We tested how organo-mineral sorption affects aquatic microbial metabolism, using organo-mineral particles containing a mix of ¹³C, ¹⁵N-labelled amino acids. We traced ¹³C and ¹⁵N retention within biofilm and suspended aggregate biomass and its mineralisation. Organo-mineral complexation restricted C and N retention within biofilms and aggregates and also their mineralisation. This reduced the efficiency with which biofilms mineralise C and N by 30 % and 6 %. By contrast, organo-minerals reduced the C and N mineralisation efficiency of suspended aggregates by 41 % and 93 %. Our findings show how organo-mineral complexation affects microbial C:N stoichiometry, potentially altering the biogeochemical fate of C and N within fluvial ecosystems.