Non-invasive on-skin sensors for brain machine interfaces with epitaxial graphene.

Objective. Brain-machine interfaces are key components for the development of hands-free, brain-controlled devices. Electroencephalogram (EEG) electrodes are particularly attractive for harvesting the neural signals in a non-invasive fashion.Approach.Here, we explore the use of epitaxial graphene (EG) grown on silicon carbide on silicon for detecting the EEG signals with high sensitivity.Main results and significance.This dry and non-invasive approach exhibits a markedly improved skin contact impedance when benchmarked to commercial dry electrodes, as well as superior robustness, allowing prolonged and repeated use also in a highly saline environment. In addition, we report the newly observed phenomenon of surface conditioning of the EG electrodes. The prolonged contact of the EG with the skin electrolytes functionalize the grain boundaries of the graphene, leading to the formation of a thin surface film of water through physisorption and consequently reducing its contact impedance more than three-fold. This effect is primed in highly saline environments, and could be also further tailored as pre-conditioning to enhance the performance and reliability of the EG sensors

Carbonaceous Materials Coated Carbon Fibre Reinforced Polymer Matrix Composites

Carbon fibre reinforced polymer composites have high mechanical properties that make them exemplary engineered materials to carry loads and stresses. Coupling fibre and matrix together require good understanding of not only fibre morphology but also matrix rheology. One way of having a strongly coupled fibre and matrix interface is to size the reinforcing fibres by means of micro- or nanocarbon materials coating on the fibre surface. Common coating materials used are carbon nanotubes and nanofibres and graphene, and more recently carbon black (colloidal particles of virtually pure elemental carbon) and graphite. There are several chemical, thermal, and electrochemical processes that are used for coating the carbonous materials onto a carbon fibre surface. Sizing of fibres provides higher interfacial adhesion between fibre and matrix and allows better fibre wetting by the surrounded matrix material. This review paper goes over numerous techniques that are used for engineering the interface between both fibre and matrix systems, which is eventually the key to better mechanical properties of the composite systems

Biochemical performance modelling of non-vegetated and vegetated vertical subsurface-flow constructed wetlands treating municipal wastewater in hot and dry climate

Wastewater treatment and subsequent effluent recycling for non-drinking purposes such as irrigation contributes to the mitigation of the pressure on freshwater resources. In this study, two vertical sub-surface flow constructed wetland (VSSF-CW) pilot plants were operated to treat municipal wastewater and their effluents were reused for irrigation purposes. One of the wetlands was vegetated with Phragmites australis (Cav.) Trin. ex Steud. (common reed) to compare its efficiency of pollutant removals with the non-vegetated system, which had the same design. COMSOL Multiphysics 3.5a was operated for the Activated Sludge Model 2 (ASM2) to predict the chemical oxygen demand (COD) and ammonia-nitrogen (NH4-N) concentrations. The effluent quality of both treatment systems was assessed for several parameters. Computer simulations show a good compliance between the measured and predicted values of COD and NH4-N for the vegetated system. The calibrated model could be effectively used to predict the behaviours of those parameters as a function of time. Moreover, the effluents of both vegetated (VFp) and non-vegetated (VF) VSSF-CW were significantly (p <  0.05) improved compared to influent. Significant (p <  0.05) effects due to the presence of P. australis were observed for removals of total suspended solids (TSS), 5-day biochemical oxygen demand (BOD5), COD, NH4-N and ortho-phosphate-phosphorus (PO4-P). However, significant increases (p <  0.05) were noted for electrical conductivity (EC), total dissolved solids (TDS), nitrate-nitrogen (NO3-N) and sulphate (SO4) of both effluents compared to the raw wastewater. Except for EC, NH4-N and SO4, all water quality parameters complied with irrigation water standards

Predominant mechanisms for the removal of nickel metal ion from aqueous solution using cement kiln dust

The experimental methodology achieved in the present study signified that the adsorption and precipitation were mainly mechanisms occurred together in the removal of nickel from aqueous solutions by sorption using cement kiln dust (CKD) byproduct as sorbent. Finding the contribution of each mechanism in the removal process and derivation an analytical model for finding the portion of precipitation were the focal points of this work. Results proved that the pure precipitation was increased with the increase of CKD dosage and metal concentration where total removal (adsorption-precipitation) ranged from 45 to 100%. The SEM micrographs of the CKD sorbent before and after sorption process certified that there was a crystal precipitates on the surface of the CKD. Also, these graphs in combination with FT-IR tests proved that [Ni(OH2)n]+2 (n=4-6) species were bonded with CKD and insoluble hydroxide species may be precipitated onto the CaO surfaces by co-precipitation, while K-O, Si-O and Ca-O groups enhanced the adsorption mechanism

Relating Neuronal to Behavioral Performance: Variability of Optomotor Responses in the Blowfly

Behavioral responses of an animal vary even when they are elicited by the same stimulus. This variability is due to stochastic processes within the nervous system and to the changing internal states of the animal. To what extent does the variability of neuronal responses account for the overall variability at the behavioral level? To address this question we evaluate the neuronal variability at the output stage of the blowfly's (Calliphora vicina) visual system by recording from motion-sensitive interneurons mediating head optomotor responses. By means of a simple modelling approach representing the sensory-motor transformation, we predict head movements on the basis of the recorded responses of motion-sensitive neurons and compare the variability of the predicted head movements with that of the observed ones. Large gain changes of optomotor head movements have previously been shown to go along with changes in the animals' activity state. Our modelling approach substantiates that these gain changes are imposed downstream of the motion-sensitive neurons of the visual system. Moreover, since predicted head movements are clearly more reliable than those actually observed, we conclude that substantial variability is introduced downstream of the visual system

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP