Microwave-assisted synthesis of multi-walled carbon nanotubes for enhanced removal of Zn(II) from wastewater

Removal of toxic metals is one of the biggest challenges in ensuring safe water for all as well as protecting the environment. Novel multi-walled carbon nanotubes (MCNTs) have been successfully synthesised by microwave techniques and improved to be an outstanding adsorbent for the removal of Zn(II) from wastewater. The adsorption of Zn(II) was studied and optimized as a function of pH, initial Zn(II) concentration, MCNT dosage, agitation speed, and adsorption time. In order to investigate the dynamic behavior of MCNTs as an adsorbent, the kinetic data were modeled using pseudo-first-order and second-order kinetic models. Different thermodynamic parameters, viz., ∆H°, ∆S° and ∆G° have also been evaluated and it has been found that the adsorption was feasible, spontaneous and endothermic in nature. Statistical analysis reveals that the optimum conditions for the highest removal (99.9 %) of Zn(II) are at pH 10, a MCNT dosage 0.05 g, an agitation speed and time of 160 rpm and 60 min, respectively, with an initial concentration of 10 mg/L. On the basis of the Langmuir model, qm was calculated to be 90.9 mg/g for microwave-synthesized MCNTs. Our results proved that MCNTs can be used as an effective Zn(II) adsorbent due to their high adsorption capacity as well as the short adsorption time needed to achieve equilibrium. Hence, MCNTs serve an important role in the removal of heavy metals from wastewater

Computational Modelling of Cancer Development and Growth:Modelling at Multiple Scales and Multiscale Modelling

MAJC and CKM gratefully acknowledge support of EPSRC grant no. EP/N014642/1 (EPSRC Centre for Multiscale Soft Tissue Mechanics – With Application to Heart & Cancer).In this paper, we present two mathematical models related to different aspects and scales of cancer growth. The first model is a stochastic spatiotemporal model of both a synthetic gene regulatory network (the example of a three-gene repressilator is given) and an actual gene regulatory network, the NF- κB pathway. The second model is a force-based individual-based model of the development of a solid avascular tumour with specific application to tumour cords, i.e. a mass of cancer cells growing around a central blood vessel. In each case, we compare our computational simulation results with experimental data. In the final discussion section, we outline how to take the work forward through the development of a multiscale model focussed at the cell level. This would incorporate key intracellular signalling pathways associated with cancer within each cell (e.g. p53–Mdm2, NF- κB) and through the use of high-performance computing be capable of simulating up to 109 cells, i.e. the tissue scale. In this way, mathematical models at multiple scales would be combined to formulate a multiscale computational model.PostprintPeer reviewe