Precipitous weakening of quartz at the α–β phase inversion

Crystalline quartz has long been identified as among the weakest of abundant crustal minerals. This weakness is particularly evident around the α–β phase inversion at 573°C, in which Si–O bonds undergo a displacive structural transformation from trigonal to hexagonal symmetry. Here we present data using indentation testing methodologies that highlight the precipitous extent of the transformational weakening. Although the indentations are localized over relatively small specimen contact areas, the data quantify the essential deformation and fracture properties of quartz in a predominantly (but not exclusively) compressive stress field, at temperatures and pressures pertinent to conditions in the earth's crust.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Preparation and electrochemical characterization of Ti-based amorphous metallic glass with high strength

Ti-based amorphous metallic glasses have excellent mechanical, physical, and chemical properties, which is an important development direction and research hotspot of metal composite reinforcement. As a stable, simple, efficient, and large-scale preparation technology of metallic powders, the gas atomization process provides an effective way of preparing amorphous metallic glasses. In this study, the controllable fabrication of a Ti-based amorphous powder, with high efficiency, has been realized by using gas atomization. The scanning electron microscope, energy-dispersive spectrometer, and X-ray diffraction are used to analyze surface morphology, element distribution, and phase structure, respectively. A microhardness tester is used to measure the mechanical property. An electrochemical workstation is used to characterize corrosion behavior. The results show that as-prepared microparticles are more uniform and exhibit good amorphous characteristics. The mechanical test shows that the hardness of amorphous powder is significantly increased as compared with that before preparation, which has the prospect of being an important part of engineering reinforced materials. Further electrochemical measurement shows that the corrosion resistance of the as-prepared sample is also significantly improved. This study has laid a solid foundation for expanding applications of Ti-based metallic glasses, especially in heavy-duty and corrosive domains.     

Psychrophilic hydrogen production from petrochemical wastewater via anaerobic sequencing batch reactor: techno-economic assessment and kinetic modelling

Independent hydrogen production from petrochemical wastewater containing mono-ethylene glycol (MEG) via anaerobic sequencing batch reactor (ASBR) was extensively assessed under psychrophilic conditions (15–25 °C). A lab-scale ASBR was operated at pH of 5.50, and different organic loading rates (OLR) of 1.00, 1.67, 2.67, and 4.00 gCOD/L/d. The hydrogen yield (HY) progressed from 134.32 ± 10.79 to 189.09 ± 22.35 mL/gMEG_initial at increasing OLR from 1.00 to 4.00 gCOD/L/d. The maximum hydrogen content of 47.44 ± 3.60% was achieved at OLR of 4.0 gCOD/L/d, while methane content remained low (17.76 ± 1.27% at OLR of 1.0 gCOD/L/d). Kinetic studies using four different mathematical models were conducted to describe the ASBR performance. Furthermore, two batch-mode experiments were performed to optimize the nitrogen supplementation as a nutrient (C/N ratio), and assess the impact of salinity (as gNaCl/L) on hydrogen production. HY substantially dropped from 62.77 ± 4.09 to 6.02 ± 0.39 mL/gMEG_initial when C/N ratio was increased from 28.5 to 114.0. Besides, the results revealed that salinity up to 10.0 gNaCl/L has a relatively low inhibitory impact on hydrogen production. Eventually, the cost/benefit analysis showed that environmental and energy recovery revenues from ASBR were optimized at OLR of 4.0 gCOD/L/d (payback period of 7.13 yrs).     

Low shear rheological behaviour of two-phase mesophase pitch

The low shear rate rheology of two phase mesophase pitches derived from coal tar pitch has been investigated. Particulate quinoline insolubles (QI) stabilised the mesophase spheres against coalescence. Viscosity measurements over the range 10–10⁶ Pa s were made at appropriate temperature ranges. Increasing shear thinning behaviour was evident with increasing mesophase content. At low mesophase contents the dominant effect on the near Newtonian viscosity was temperature but at higher contents it was the shear rate; temperature dependence declined to near zero. The data indicated that agglomeration could be occurring at intermediate mesophase volume fractions, 0.2–0.3. The Krieger–Dougherty function and its emulsion analogue indicated that in this region the mesophase pitch emulsions actually behaved like ‘hard’ sphere systems and the effective volume fraction was estimated as a function of shear rate illustrating the change in extent of agglomeration. At the higher volume fractions approaching the maximum packing fraction, which could only be measured at higher temperatures, the shear thinning behaviour changed in character and it is considered that this is possibly due to shear induced deformation and breakup of dispersed drops in the shear field.     

Strategic planning optimization for natural gas to liquid transportation fuel (GTL) systems

A strategic planning optimization model is proposed for a network of natural gas to liquids (GTL) systems, and it is solved using a rolling horizon strategy. The model formulation determines the strategic and tactical decisions of the GTL supply chain over a long time horizon. The decisions to build new GTL refineries may be made over the span of 30 years and their operations cover the span of 60 years. Multiple capacities of GTL refineries (i.e., 1, 5, 10, 50, and 200 thousand barrels per day) that produce gasoline, diesel, and kerosene commensurate to the United States demand ratio may exist in the network. The parameter inputs include the locations, availabilities, and prices of natural gas in the United States discretized by county, the delivery locations of fuel products, and the transportation costs of every input and output of the refinery, defined for each time period. Formulated as a large-scale mixed-integer linear optimization (MILP) model, the problem is solved using a rolling horizon strategy for tractability. Case studies on the state of Pennsylvania are presented for different planning schemes and their impact on the economic performance of the GTL network is discussed.     

A mineralogical approach to evaluating laboratory scale acid rock drainage characterisation tests

Effective management of the risks associated with acid rock drainage (ARD) requires the ability to identify material with a potential to generate ARD reliably. With the increasing prevalence of quantitative mineralogy (Quantitative XRD, auto-SEM), opportunity exists to use mineralogy at all stages in ARD characterisation and prediction. This study uses a mineralogical approach across the head grade samples and the residues obtained under leach conditions of several common ARD characterisation tests (Acid Neutralising Capacity, Net Acid Generation), as well as the University of Cape Town (UCT) biokinetic test to evaluate the extent to which acid-neutralising minerals react. The results show the contribution of the carbonates to the acid neutralising capacity, as well as the partial dissolution of intermediate weathering silicate minerals such as chlorite and mica.     

A GIS plug-in for Bayesian belief networks: Towards a transparent software framework to assess and visualise uncertainties in ecosystem service mapping

The complexity and spatial heterogeneity of ecosystem processes driving ecosystem service delivery require spatially explicit models that take into account the different parameters affecting those processes. Current attempts to model ecosystem service delivery on a broad, regional scale often depend on indicator-based approaches that are generally not able to fully capture the complexity of ecosystem processes. Moreover, they do not allow quantification of uncertainty on their predictions. In this paper, we discuss a QGIS plug-in which promotes the use of Bayesian belief networks for regional modelling and mapping of ecosystem service delivery and associated uncertainties. Different types of specific Bayesian belief network output maps, delivered by the plug-in, are discussed and their decision support capacities are evaluated. This plug-in, used in combination with firmly developed Bayesian belief networks, has the potential to add value to current spatial ecosystem service accounting methods. The plug-in can also be used in other research domains dealing with spatial data and uncertainty.     

Significant spatial co-distribution pattern discovery

Given instances (spatial points) of different spatial features (categories), significant spatial co-distribution pattern discovery aims to find subsets of spatial features whose spatial distributions are statistically significantly similar to each other. Discovering significant spatial co-distribution patterns is important for many application domains such as identifying spatial associations between diseases and risk factors in spatial epidemiology. Previous methods mostly associated spatial features whose instances are frequently located together; however, this does not necessarily indicate a similarity in the spatial distributions between different features. Thus, this paper defines the significant spatial co-distribution pattern discovery problem and subsequently develops a novel method to solve it effectively. First, we propose a new measure, dissimilarity index, to quantify the difference between spatial distributions of different features under the spatial neighbor relation and then employ it in a distribution clustering method to detect candidate spatial co-distribution patterns. To further remove spurious patterns that occur accidentally, the validity of each candidate spatial co-distribution pattern is verified through a significance test under the null hypothesis that spatial distributions of different features are independent of each other. To model the null hypothesis, a distribution shift-correction method is presented by randomizing the relationships between different features and maintaining spatial structure of each feature (e.g., spatial auto-correlation). Comparisons with baseline methods using synthetic datasets demonstrate the effectiveness of the proposed method. A case study identifying co-morbidities in central Colorado is also presented to illustrate the real-world applicability of the proposed method.     

Public-sector reform: Lessons from the privatisation experiment in Greece

This paper explores the process of public sector reform in Greece through the lens of privatisation. It is suggested that the transformation of the domestic post-war interventionist state into the current market-oriented paradigm has been disrupted and dependent on changing reform rationales. Along with the effect of historical dynamics on the direction and scale of change, the explanatory power of external determinants of reform is stressed. Findings reflect a direct linkage between the intensity of external pressure and the pace of reforms. The sustainability of gradual privatisation reforms seems more certain than the outcomes of fast-track privatisations under policy conditionality.