Options for achieving a 50% cut in industrial carbon emissions by 2050.

Carbon emissions from industry are dominated by production of goods in steel, cement plastic, paper, and aluminum. Demand for these materials is anticipated to double at least by 2050, by which time global carbon emissions must be reduced by at least 50%. To evaluate the challenge of meeting this target the global flows of these materials and their associated emissions are projected to 2050 under five technical scenarios. A reference scenario includes all existing and emerging efficiency measures but cannot provide sufficient reduction. The application of carbon sequestration to primary production proves to be sufficient only for cement The emissions target can always be met by reducing demand, for instance through product life extension, material substitution, or "light-weighting". Reusing components shows significant potential particularly within construction. Radical process innovation may also be possible. The results show that the first two strategies, based on increasing primary production, cannot achieve the required emissions reductions, so should be balanced by the vigorous pursuit of material efficiency to allow provision of increased material services with reduced primary production.

ZnO based SAW and FBAR devices for lab-on-a chip applications

Acoustic wave devices were fabricated incorporating ZnO films deposited using both a standard rf magnetronand a novel High Target Utilisation (HiTUS) Sputtering System. Our results demonstrated the feasibility of using a single SAW-based actuation mechanism for both microfluidics and sensing. To further improve the sensitivity of our bio-sensors we have also investigated the use of Thin Film Bulk Acoustic Resonators.

Dopamine and performance in a reinforcement learning task: evidence from Parkinson's disease.

The role dopamine plays in decision-making has important theoretical, empirical and clinical implications. Here, we examined its precise contribution by exploiting the lesion deficit model afforded by Parkinson's disease. We studied patients in a two-stage reinforcement learning task, while they were ON and OFF dopamine replacement medication. Contrary to expectation, we found that dopaminergic drug state (ON or OFF) did not impact learning. Instead, the critical factor was drug state during the performance phase, with patients ON medication choosing correctly significantly more frequently than those OFF medication. This effect was independent of drug state during initial learning and appears to reflect a facilitation of generalization for learnt information. This inference is bolstered by our observation that neural activity in nucleus accumbens and ventromedial prefrontal cortex, measured during simultaneously acquired functional magnetic resonance imaging, represented learnt stimulus values during performance. This effect was expressed solely during the ON state with activity in these regions correlating with better performance. Our data indicate that dopamine modulation of nucleus accumbens and ventromedial prefrontal cortex exerts a specific effect on choice behaviour distinct from pure learning. The findings are in keeping with the substantial other evidence that certain aspects of learning are unaffected by dopamine lesions or depletion, and that dopamine plays a key role in performance that may be distinct from its role in learning.

Dopamine and performance in a reinforcement learning task: Evidence from Parkinson's disease

The role dopamine plays in decision-making has important theoretical, empirical and clinical implications. Here, we examined its precise contribution by exploiting the lesion deficit model afforded by Parkinson's disease. We studied patients in a two-stage reinforcement learning task, while they were ON and OFF dopamine replacement medication. Contrary to expectation, we found that dopaminergic drug state (ON or OFF) did not impact learning. Instead, the critical factor was drug state during the performance phase, with patients ON medication choosing correctly significantly more frequently than those OFF medication. This effect was independent of drug state during initial learning and appears to reflect a facilitation of generalization for learnt information. This inference is bolstered by our observation that neural activity in nucleus accumbens and ventromedial prefrontal cortex, measured during simultaneously acquired functional magnetic resonance imaging, represented learnt stimulus values during performance. This effect was expressed solely during the ON state with activity in these regions correlating with better performance. Our data indicate that dopamine modulation of nucleus accumbens and ventromedial prefrontal cortex exerts a specific effect on choice behaviour distinct from pure learning. The findings are in keeping with the substantial other evidence that certain aspects of learning are unaffected by dopamine lesions or depletion, and that dopamine plays a key role in performance that may be distinct from its role in learning. © 2012 The Author.

Estimation of soil properties and deformations in staged constructions based on mcmc method

This paper presents a Bayesian probabilistic framework to assess soil properties and model uncertainty to better predict excavation-induced deformations using field deformation data. The potential correlations between deformations at different depths are accounted for in the likelihood function needed in the Bayesian approach. The proposed approach also accounts for inclinometer measurement errors. The posterior statistics of the unknown soil properties and the model parameters are computed using the Delayed Rejection (DR) method and the Adaptive Metropolis (AM) method. As an application, the proposed framework is used to assess the unknown soil properties of multiple soil layers using deformation data at different locations and for incremental excavation stages. The developed approach can be used for the design of optimal revisions for supported excavation systems. © 2010 ASCE.

Stretching-assembled nanowires for organic-based thin film transistors

We demonstrate a stretched contact-printing technique to assemble one-dimensional nanostructures with controlled density and orientation. Over 90% nanowires are highly aligned along the primary stretching direction. Specifically, The hybrid inorganic-organic TFTs based on a parallel-aligned nanowire network and a semiconducting polymer reveal a significant positive enhancement in transistor performance and air-stability.

CNTs & graphene for field emission applications

This paper details the use of carbon nanotubes and graphene for key field emission applications. Herein we describe the growth of nanotubes and their optimization for use in electron microscopes, field emission displays and x-ray sources. We also present a novel edge-emitting graphene based structure for large area electron emission displays.

Double-wall carbon nanotubes for wide-band, ultrafast pulse generation.

We demonstrate wide-band ultrafast optical pulse generation at 1, 1.5, and 2 μm using a single-polymer composite saturable absorber based on double-wall carbon nanotubes (DWNTs). The freestanding optical quality polymer composite is prepared from nanotubes dispersed in water with poly(vinyl alcohol) as the host matrix. The composite is then integrated into ytterbium-, erbium-, and thulium-doped fiber laser cavities. Using this single DWNT-polymer composite, we achieve 4.85 ps, 532 fs, and 1.6 ps mode-locked pulses at 1066, 1559, and 1883 nm, respectively, highlighting the potential of DWNTs for wide-band ultrafast photonics.