NMR methods for characterizing the pore structures and hydrogen storage properties of microporous carbons.

(1)H NMR spectroscopy is used to investigate a series of microporous activated carbons derived from a poly(ether ether ketone) (PEEK) precursor with varying amounts of burnoff (BO). In particular, properties relevant to hydrogen storage are evaluated such as pore structure, average pore size, uptake, and binding energy. High-pressure NMR with in situ H(2) loading is employed with H(2) pressure ranging from 100 Pa to 10 MPa. An N(2)-cooled cryostat allows for NMR isotherm measurements at both room temperature ( approximately 290 K) and 100 K. Two distinct (1)H NMR peaks appear in the spectra which represent the gaseous H(2) in intergranular pores and the H(2) residing in micropores. The chemical shift of the micropore peak is observed to evolve with changing pressure, the magnitude of this effect being correlated to the amount of BO and therefore the structure. This is attributed to the different pressure dependence of the amount of adsorbed and non-adsorbed molecules within micropores, which experience significantly different chemical shifts due to the strong distance dependence of the ring current effect. In pores with a critical diameter of 1.2 nm or less, no pressure dependence is observed because they are not wide enough to host non-adsorbed molecules; this is the case for samples with less than 35% BO. The largest estimated pore size that can contribute to the micropore peak is estimated to be around 2.4 nm. The total H(2) uptake associated with pores of this size or smaller is evaluated via a calibration of the isotherms, with the highest amount being observed at 59% BO. Two binding energies are present in the micropores, with the lower, more dominant one being on the order of 5 kJ mol(-1) and the higher one ranging from 7 to 9 kJ mol(-1).

Physical and economic potential of geological CO2 storage in saline aquifers.

Carbon sequestration in sandstone saline reservoirs holds great potential for mitigating climate change, but its storage potential and cost per ton of avoided CO2 emissions are uncertain. We develop a general model to determine the maximum theoretical constraints on both storage potential and injection rate and use it to characterize the economic viability of geosequestration in sandstone saline aquifers. When applied to a representative set of aquifer characteristics, the model yields results that compare favorably with pilot projects currently underway. Over a range of reservoir properties, maximum effective storage peaks at an optimal depth of 1600 m, at which point 0.18-0.31 metric tons can be stored per cubic meter of bulk volume of reservoir. Maximum modeled injection rates predict minima for storage costs in a typical basin in the range of $2-7/ ton CO2 (2005 U.S.$) depending on depth and basin characteristics in our base-case scenario. Because the properties of natural reservoirs in the United States vary substantially, storage costs could in some cases be lower or higher by orders of magnitude. We conclude that available geosequestration capacity exhibits a wide range of technological and economic attractiveness. Like traditional projects in the extractive industries, geosequestration capacity should be exploited starting with the low-cost storage options first then moving gradually up the supply curve.

The upstream enhancer elements of the G6PC promoter are critical for optimal G6PC expression in murine glycogen storage disease type Ia.

Glycogen storage disease type-Ia (GSD-Ia) patients deficient in glucose-6-phosphatase-α (G6Pase-α or G6PC) manifest impaired glucose homeostasis characterized by fasting hypoglycemia, growth retardation, hepatomegaly, nephromegaly, hyperlipidemia, hyperuricemia, and lactic acidemia. Two efficacious recombinant adeno-associated virus pseudotype 2/8 (rAAV8) vectors expressing human G6Pase-α have been independently developed. One is a single-stranded vector containing a 2864-bp of the G6PC promoter/enhancer (rAAV8-GPE) and the other is a double-stranded vector containing a shorter 382-bp minimal G6PC promoter/enhancer (rAAV8-miGPE). To identify the best construct, a direct comparison of the rAAV8-GPE and the rAAV8-miGPE vectors was initiated to determine the best vector to take forward into clinical trials. We show that the rAAV8-GPE vector directed significantly higher levels of hepatic G6Pase-α expression, achieved greater reduction in hepatic glycogen accumulation, and led to a better toleration of fasting in GSD-Ia mice than the rAAV8-miGPE vector. Our results indicated that additional control elements in the rAAV8-GPE vector outweigh the gains from the double-stranded rAAV8-miGPE transduction efficiency, and that the rAAV8-GPE vector is the current choice for clinical translation in human GSD-Ia.

Canary grass : variations in grain yield and other agronomically important features in response to different plant densities

p.43-55

Canary grass : variations in grain yield and other agronomically important features in response to different plant densities

p.43-55

Application of simulation technologies in the analysis of granular material behaviour during transport and storage

Problems in the preservation of the quality of granular material products are complex and arise from a series of sources during transport and storage. In either designing a new plant or, more likely, analysing problems that give rise to product quality degradation in existing operations, practical measurement and simulation tools and technologies are required to support the process engineer. These technologies are required to help in both identifying the source of such problems and then designing them out. As part of a major research programme on quality in particulate manufacturing computational models have been developed for segregation in silos, degradation in pneumatic conveyors, and the development of caking during storage, which use where possible, micro-mechanical relationships to characterize the behaviour of granular materials. The objective of the work presented here is to demonstrate the use of these computational models of unit processes involved in the analysis of large-scale processes involving the handling of granular materials. This paper presents a set of simulations of a complete large-scale granular materials handling operation, involving the discharge of the materials from a silo, its transport through a dilute-phase pneumatic conveyor, and the material storage in a big bag under varying environmental temperature and humidity conditions. Conclusions are drawn on the capability of the computational models to represent key granular processes, including particle size segregation, degradation, and moisture migration caking.

The UK WTC 9/11 evacuation study: methodologies used in the elicitation and storage of human factors data

This paper describes the methodologies employed in the collection and storage of first-hand accounts of evacuation experiences derived from face-to-face interviews with evacuees from the World Trade Center (WTC) Twin Towers complex on 11 September 2001. In particular the paper describes the development of the High-rise Evacuation Evaluation Database (HEED). This is a flexible qualitative research tool which contains the full transcribed interview accounts and coded evacuee experiences extracted from those transcripts. The data and information captured and stored in the HEED database is not only unique, but it provides a means to address current and emerging issues relating to human factors associated with the evacuation of high-rise buildings.

Methodologies employed in the collection, retrieval and storage of human factors information derived from first hand accounts of survivors of the WTC disaster of 11 September 2001

This article provides a broad overview of project HEED (High-rise Evacuation Evaluation Database) and the methodologies employed in the collection and storage of first-hand accounts of evacuation experiences derived from face-to-face interviews of evacuees from the World Trade Center (WTC) Twin Towers complex on September 11, 2001. In particular, the article describes the development of the HEED database. This is a flexible research tool which contains qualitative type data in the form of coded evacuee experiences along with the full interview transcripts. The data and information captured and stored in the HEED database is not only unique, but provides a means to address current and emerging issues relating to human factors associated with the evacuation of high-rise buildings