Now showing items 1-20 of 420

• Bordered Constructions of Self-Dual Codes from Group Rings and New Extremal Binary Self-Dual Codes

(Elsevier, 2019)
We introduce a bordered construction over group rings for self-dual codes. We apply the constructions over the binary field and the ring $\F_2+u\F_2$, using groups of orders 9, 15, 21, 25, 27, 33 and 35 to find extremal binary self-dual codes of lengths 20, 32, 40, 44, 52, 56, 64, 68, 88 and best known binary self-dual codes of length 72. In particular we obtain 41 new binary extremal self-dual codes of length 68 from groups of orders 15 and 33 using neighboring and extensions. All the numerical results are tabulated throughout the paper.
• Appearance Modeling of Living Human Tissues

(Wiley, 2019)
The visual fidelity of realistic renderings in Computer Graphics depends fundamentally upon how we model the appearance of objects resulting from the interaction between light and matter reaching the eye. In this paper, we survey the research addressing appearance modeling of living human tissue. Among the many classes of natural materials already researched in Computer Graphics, living human tissues such as blood and skin have recently seen an increase in attention from graphics research. There is already an incipient but substantial body of literature on this topic, but we also lack a structured review as presented here. We introduce a classification for the approaches using the four types of human tissues as classifiers. We show a growing trend of solutions that use first principles from Physics and Biology as fundamental knowledge upon which the models are built. The organic quality of visual results provided by these Biophysical approaches is mainly determined by the optical properties of biophysical components interacting with light. Beyond just picture making, these models can be used in predictive simulations, with the potential for impact in many other areas.
• Optimal convergence rates for semidiscrete finite element approximations of linear space-fractional partial differential equations under minimal regularity assumptions

(Elsevier, 2018-12-17)
We consider the optimal convergence rates of the semidiscrete finite element approximations for solving linear space-fractional partial differential equations by using the regularity results for the fractional elliptic problems obtained recently by Jin et al. \cite{jinlazpasrun} and Ervin et al. \cite{ervheuroo}. The error estimates are proved by using two approaches. One approach is to apply the duality argument in Johnson \cite{joh} for the heat equation to consider the error estimates for the linear space-fractional partial differential equations. This argument allows us to obtain the optimal convergence rates under the minimal regularity assumptions for the solution. Another approach is to use the approximate solution operators of the corresponding fractional elliptic problems. This argument can be extended to consider more general linear space-fractional partial differential equations. Numerical examples are given to show that the numerical results are consistent with the theoretical results.
• Data-driven selection and parameter estimation for DNA methylation mathematical models

(Elsevier, 2019-01-10)
Epigenetics is coming to the fore as a key process which underpins health. In particular emerging experimental evidence has associated alterations to DNA methylation status with healthspan and aging. Mammalian DNA methylation status is maintained by an intricate array of biochemical and molecular processes. It can be argued changes to these fundamental cellular processes ultimately drive the formation of aberrant DNA methylation patterns, which are a hallmark of diseases, such as cancer, Alzheimer's disease and cardiovascular disease. In recent years mathematical models have been used as e ective tools to help advance our understanding of the dynamics which underpin DNA methylation. In this paper we present linear and nonlinear models which encapsulate the dynamics of the molecular mechanisms which de ne DNA methylation. Applying a recently developed Bayesian algorithm for parameter estimation and model selection, we are able to estimate distributions of parameters which include nominal parameter values. Using limited noisy observations, the method also identifed which methylation model the observations originated from, signaling that our method has practical applications in identifying what models best match the biological data for DNA methylation.
• Data-driven selection and parameter estimation for DNA methylation mathematical models.

(2019-01-08)
Epigenetics is coming to the fore as a key process which underpins health. In particular emerging experimental evidence has associated alterations to DNA methylation status with healthspan and aging. Mammalian DNA methylation status is maintained by an intricate array of biochemical and molecular processes. It can be argued changes to these fundamental cellular processes ultimately drive the formation of aberrant DNA methylation patterns, which are a hallmark of diseases, such as cancer, Alzheimer's disease and cardiovascular disease. In recent years mathematical models have been used as effective tools to help advance our understanding of the dynamics which underpin DNA methylation. In this paper we present linear and nonlinear models which encapsulate the dynamics of the molecular mechanisms which define DNA methylation. Applying a recently developed Bayesian algorithm for parameter estimation and model selection, we are able to estimate distributions of parameters which include nominal parameter values. Using limited noisy observations, the method also identified which methylation model the observations originated from, signaling that our method has practical applications in identifying what models best match the biological data for DNA methylation. [Abstract copyright: Copyright © 2019. Published by Elsevier Ltd.]
• Numerical Solution of Fractional Differential Equations and their Application to Physics and Engineering

(University of Chester, 2018-12-03)
This dissertation presents new numerical methods for the solution of fractional differential equations of single and distributed order that find application in the different fields of physics and engineering. We start by presenting the relationship between fractional derivatives and processes like anomalous diffusion, and, we then develop new numerical methods for the solution of the time-fractional diffusion equations. The first numerical method is developed for the solution of the fractional diffusion equations with Neumann boundary conditions and the diffusivity parameter depending on the space variable. The method is based on finite differences, and, we prove its convergence (convergence order of O(Δx² + Δt²<sup>-α</sup>), 0 < α < 1) and stability. We also present a brief description of the application of such boundary conditions and fractional model to real world problems (heat flux in human skin). A discussion on the common substitution of the classical derivative by a fractional derivative is also performed, using as an example the temperature equation. Numerical methods for the solution of fractional differential equations are more difficult to develop when compared to the classical integer-order case, and, this is due to potential singularities of the solution and to the nonlocal properties of the fractional differential operators that lead to numerical methods that are computationally demanding. We then study a more complex type of equations: distributed order fractional differential equations where we intend to overcome the second problem on the numerical approximation of fractional differential equations mentioned above. These equations allow the modelling of more complex anomalous diffusion processes, and can be viewed as a continuous sum of weighted fractional derivatives. Since the numerical solution of distributed order fractional differential equations based on finite differences is very time consuming, we develop a new numerical method for the solution of the distributed order fractional differential equations based on Chebyshev polynomials and present for the first time a detailed study on the convergence of the method. The third numerical method proposed in this thesis aims to overcome both problems on the numerical approximation of fractional differential equations. We start by solving the problem of potential singularities in the solution by presenting a method based on a non-polynomial approximation of the solution. We use the method of lines for the numerical approximation of the fractional diffusion equation, by proceeding in two separate steps: first, spatial derivatives are approximated using finite differences; second, the resulting system of semi-discrete ordinary differential equations in the initial value variable is integrated in time with a non-polynomial collocation method. This numerical method is further improved by considering graded meshes and an hybrid approximation of the solution by considering a non-polynomial approximation in the first sub-interval which contains the origin in time (the point where the solution may be singular) and a polynomial approximation in the remaining intervals. This way we obtain a method that allows a faster numerical solution of fractional differential equations (than the method obtained with non-polynomial approximation) and also takes into account the potential singularity of the solution. The thesis ends with the main conclusions and a discussion on the main topics presented along the text, together with a proposal of future work.
• Disrupting folate metabolism reduces the capacity of bacteria in exponential growth to develop persisters to antibiotics

(Microbiology Society, 2018-11-01)
Bacteria can survive high doses of antibiotics through stochastic phenotypic diversification. We present initial evidence that folate metabolism could be involved with the formation of persisters. The aberrant expression of the folate enzyme gene fau seems to reduce the incidence of persisters to antibiotics. Folate-impaired bacteria had a lower generation rate for persisters to the antibiotics ampicillin and ofloxacin. Persister bacteria were detectable from the outset of the exponential growth phase in the complex media. Gene expression analyses tentatively showed distinctive profiles in exponential growth at times when bacteria persisters were observed. Levels of persisters were assessed in bacteria with altered, genetically and pharmacologically, folate metabolism. This work shows that by disrupting folate biosynthesis and usage, bacterial tolerance to antibiotics seems to be diminished. Based on these findings there is a possibility that bacteriostatic antibiotics such as anti-folates could have a role to play in clinical settings where the incidence of antibiotic persisters seems to drive recalcitrant infections.
• Towards Organisational Learning Enhancement: Assessing Software Engineering Practice

(Emerald Publishing Limited, 2018-12-17)
• Purpose – Issues surrounding knowledge management, knowledge transfer and learning within organisations challenge continuity and resilience in the face of changing environments. While initiatives are principally applied within large organisations, there is scope to assess how the processes are handled within small and medium enterprises (SMEs) and to consider how they might be enhanced. This paper presents an evaluation of practice within an evolving software development unit to determine what has been learned and how the knowledge acquired has been utilised to further organisational development. These results provide the basis for the design and implementation of a proposed support tool to enhance professional practice. • Design/methodology/approach – A small software development unit, which has successfully delivered bespoke systems since its establishment a number of years ago, was selected for analysis. The unit operates as a team whose actions and behaviours were identified and validated by the following means: in-depth interviews were carried out with each member of the team to elicit an understanding of individual and collective development. Interview data were recorded and transcribed and subjected to qualitative analysis to identify key themes underpinning knowledge acquisition and utilisation. Samples of project documentation were scrutinised to corroborate interview data. After analysing the data, a focus-group meeting was held to validate the results and to generate further insights into learning within the team. • Findings - Qualitative analysis of the data revealed key changes in thinking and practice within the team as well as insight into the development of individual and collective contextual knowledge, tacit understanding and learning. This analysis informed the proposal of a bespoke, lightweight, web-based system to support knowledge capture and organisational learning (OL). This approach has the potential to promote resilience and to enhance practice in similar small or start-up enterprises. • Research limitations/implications – Purposeful sampling was used in selecting a small software development team. This enabled in-depth interviewing of all members of the team. This offered a rich environment from which to derive awareness and understanding of individual and collective knowledge acquisition and learning. Focusing on a single small enterprise limits the extent to which the findings can be generalised. However, the research provides evidence of effective practice and learning and has identified themes for the development of a support tool. This approach can be extended to similar domains to advance research into learning and development. • Practical implications – Results of the work undertaken so far have generated promising foundations for the proposed support tool. This offers software developers a system within which they can reflect upon, and record, key learning events affecting technical, managerial and professional practice. • Originality/value – Small enterprises have limited resources to support OL. The qualitative research undertaken so far has yielded valuable insight into the successful development of a single software development team. The construction of a support tool to enhance knowledge acquisition and learning has the capacity to consolidate valuable, and potentially scarce, expertise. It also has the potential to facilitate further research to determine how the prototype might be extended or revised to improve its contribution to the team’s development.
• Evolutionary Robot Swarm Cooperative Retrieval

(Springer, 2018-07-07)
In nature bees and leaf-cutter ants communicate to improve cooperation during food retrieval. This research aims to model communication in a swarm of auton-omous robots. When food is identified robot communication is emitted within a limited range. Other robots within the range receive the communication and learn of the location and size of the food source. The simulation revealed that commu-nication improved the rate of cooperative food retrieval tasks. However a counter-productive chain reaction can occur when robots repeat communications from other robots causing cooperation errors. This can lead to a large number of robots travelling towards the same food source at the same time. The food becomes de-pleted, before some robots have arrived. Several robots continue to communicate food presence, before arriving at the food source to find it gone. Nature-inspired communication can enhance swarm behaviour without requiring a central control-ler and may be useful in autonomous drones or vehicles.
• Rapid, Chemical-Free Generation of Optically Scattering Structures in Poly(ethylene terephthalate) Using a CO2 Laser for Lightweight and Flexible Photovoltaic Applications

(Hindawi, 2018-12-16)
Highly light scattering structures have been generated in a poly(ethylene terephthalate) (PET) film using a CO2 laser. The haze, and in some cases the transparency, of the PET films have been improved by varying the processing parameters of the laser (namely, scanning velocity, laser output power, and spacing between processed tracks). When compared with the unprocessed PET, the haze has improved from an average value of 3.26% to a peak of 55.42%, which equates to an absolute improvement of 52.16% or a 17-fold increase. In addition to the optical properties, the surfaces have been characterised using optical microscopy and mapped with an optical profilometer. Key surface parameters that equate to the amount and structure of surface roughness and features have been analysed. The CO2 laser generates microstructures at high speed, without affecting the bulk properties of the material, and is inherently a chemical-free process making it particularly applicable for use in industry, fitting well with the high-throughput, roll to roll processes associated with the production of flexible organic photovoltaic devices.
• 3D printed graphene based energy storage devices

(Springer Nature, 2017-03-03)
3D printing technology provides a unique platform for rapid prototyping of numerous applications due to its ability to produce low cost 3D printed platforms. Herein, a graphene-based polylactic acid filament (graphene/PLA) has been 3D printed to fabricate a range of 3D disc electrode (3DE) configurations using a conventional RepRap fused deposition moulding (FDM) 3D printer, which requires no further modification/ex-situ curing step. To provide proof-of-concept, these 3D printed electrode architectures are characterised both electrochemically and physicochemically and are advantageously applied as freestanding anodes within Li-ion batteries and as solid-state supercapacitors. These freestanding anodes neglect the requirement for a current collector, thus offering a simplistic and cheaper alternative to traditional Li-ion based setups. Additionally, the ability of these devices’ to electrochemically produce hydrogen via the hydrogen evolution reaction (HER) as an alternative to currently utilised platinum based electrodes (with in electrolysers) is also performed. The 3DE demonstrates an unexpectedly high catalytic activity towards the HER (−0.46 V vs. SCE) upon the 1000th cycle, such potential is the closest observed to the desired value of platinum at (−0.25 V vs. SCE). We subsequently suggest that 3D printing of graphene-based conductive filaments allows for the simple fabrication of energy storage devices with bespoke and conceptual designs to be realised.
• Perovskite Srx(Bi1-xNa0.97-xLi0.03)0.5TiO3 ceramics with polar nano regions for high power energy storage

(Elsevier, 2018-06-06)
Dielectric capacitors are very attractive for high power energy storage. However, the low energy density of these capacitors, which is mainly limited by the dielectric materials, is still the bottleneck for their applications. In this work, lead-free single-phase perovskite Srx(Bi1-xNa0.97-xLi0.03)0.5TiO3 (x=0.30 and 0.38) bulk ceramics, prepared using solid-state reaction method, were carefully studied for the dielectric capacitor application. Polar nano regions (PNRs) were created in this material using co-substitution at A-site to enable relaxor behaviour with low remnant polarization (Pr) and high maximum polarization (Pmax). Moreover, Pmax was further increased due to reversible electric field induced phase transitions. Comprehensive structural and electrical studies were performed to confirm the PNRs and the reversible phase transitions. And finally a high energy density (1.70 J/cm3) with an excellent efficiency (87.2%) was achieved using the contribution of PNRs and field-induced transitions in this material, making it among the best performing lead-free dielectric ceramic bulk material for high energy storage.
• Pencil it in: Exploring the Feasibility of Hand-Drawn Pencil Electrochemical Sensors and their Direct Comparison to Screen-Printed Electrodes

(MDPI, 2016-08-29)
We explore the fabrication, physicochemical characterisation (SEM, Raman, EDX and XPS) and electrochemical application of hand-drawn pencil electrodes (PDEs) upon an ultra-flexible polyester substrate; investigating the number of draws (used for their fabrication), the pencil grade utilised (HB to 9B) and the electrochemical properties of an array of batches (i.e, pencil boxes). Electrochemical characterisation of the PDEs, using different batches of HB grade pencils, is undertaken using several inner- and outer-sphere redox probes and is critically compared to screen-printed electrodes (SPEs). Proof-of-concept is demonstrated for the electrochemical sensing of dopamine and acetaminophen using PDEs, which are found to exhibit competitive limits of detection (3σ) upon comparison to SPEs. Nonetheless, it is important to note that a clear lack of reproducibility was demonstrated when utilising these PDEs fabricated using the HB pencils from different batches. We also explore the suitability and feasibility of a pencil-drawn reference electrode compared to screen-printed alternatives, to see if one can draw the entire sensing platform. This article reports a critical assessment of these PDEs against that of its screen-printed competitors, questioning the overall feasibility of PDEs’ implementation as a sensing platform
• Enhancement in Interfacial Adhesion of Ti/Polyetheretherketone by Electrophoretic Deposition of Graphene Oxide

(Wiley, 2018-11-25)
• Controller Design Methodology for Sustainable Local Energy Systems

(University of Chester, 2018-11-15)
Commercial Buildings and complexes are no longer just national heat and power network energy loads, but they are becoming part of a smarter grid by including their own dedicated local heat and power generation. They do this by utilising both heat and power networks/micro-grids. A building integrated approach of Combined Heat and Power (CHP) generation with photovoltaic power generation (PV) abbreviated as CHPV is emerging as a complementary energy supply solution to conventional (i.e. national grid based) gas and electricity grid supplies in the design of sustainable commercial buildings and communities. The merits for the building user/owner of this approach are: to reduce life time energy running costs; reduce carbon emissions to contribute to UK’s 2020/2030 climate change targets; and provide a more flexible and controllable local energy system to act as a dynamic supply and/or load to the central grid infrastructure. The energy efficiency and carbon dioxide (CO2) reductions achievable by CHP systems are well documented. The merits claimed by these solutions are predicated on the ability of these systems being able to satisfy: perfect matching of heat and power supply and demand; ability at all times to maintain high quality power supply; and to be able to operate with these constraints in a highly dynamic and unpredictable heat and power demand situation. Any circumstance resulting in failure to guarantee power quality or matching of supply and demand will result in a degradation of the achievable energy efficiency and CO2 reduction. CHP based local energy systems cannot rely on large scale diversity of demand to create a relatively easy approach to supply and demand matching (i.e. as in the case of large centralised power grid infrastructures). The diversity of demand in a local energy system is both much greater than the centralised system and is also specific to the local system. It is therefore essential that these systems have robust and high performance control systems to ensure supply and demand matching and high power quality can be achieved at all times. Ideally this same control system should be able to make best use of local energy system energy storage to enable it to be used as a flexible, highly responsive energy supply and/or demand for the centralised infrastructure. In this thesis, a comprehensive literature survey has identified that there is no scientific and rigorous method to assess the controllability or the design of control systems for these local energy systems. Thus, the main challenge of the work described in this thesis is that of a controller design method and modelling approach for CHP based local energy systems. Specifically, the main research challenge for the controller design and modelling methodology was to provide an accurate and stable system performance to deliver a reliable tracking of power drawn/supplied to the centralised infrastructure whilst tracking the require thermal comfort in the local energy systems buildings. In the thesis, the CHPV system has been used as a case study. A CHPV based solution provides all the benefits of CHP combined with the near zero carbon building/local network integrated PV power generation. CHPV needs to be designed to provide energy for the local buildings’ heating, dynamic ventilating system and air-conditioning (HVAC) facilities as well as all electrical power demands. The thesis also presents in addition to the controller design and modelling methodology a novel CHPV system design topology for robust, reliable and high-performance control of building temperatures and energy supply from the local energy system. The advanced control system solution aims to achieve desired building temperatures using thermostatic control whilst simultaneously tracking a specified national grid power demand profile. The theory is innovative as it provides a stability criterion as well as guarantees to track a specified dynamic grid connection demand profile. This research also presents: design a dynamic MATLAB simulation model for a 5-building zone commercial building to show the efficacy of the novel control strategy in terms of: delivering accurate thermal comfort and power supply; reducing the amount of CO2 emissions by the entire energy system; reducing running costs verses national rid/conventional approaches. The model was developed by inspecting the functional needs of 3 local energy system case studies which are also described in the thesis. The CHPV system is combined with supplementary gas boiler for additional heating to guarantee simultaneous tracking of all the zones thermal comfort requirements whilst simultaneously tracking a specified national grid power demand using a Photovoltaics array to supply the system with renewable energy to reduce amount of CO2 emission. The local energy system in this research can operate in any of three modes (Exporting, Importing, Island). The emphasise of the thesis modelling method has been verified to be applicable to a wide range of case studies described in the thesis chapter 3. This modelling framework is the platform for creating a generic controlled design methodology that can be applied to all these case studies and beyond, including Local Energy System (LES) in hotter climates that require a cooling network using absorption chillers. In the thesis in chapter 4 this controller design methodology using the modelling framework is applied to just one case study of Copperas Hill. Local energy systems face two types of challenges: technical and nontechnical (such as energy economics and legislation). This thesis concentrates solely on the main technical challenges of a local energy system that has been identified as a gap in knowledge in the literature survey. The gap identified is the need for a controller design methodology to allow high performance and safe integration of the local energy system with the national grid infrastructure and locally installed renewables. This integration requires the system to be able to operate at high performance and safely in all different modes of operation and manage effectively the multi-vector energy supply system (e.g. simultaneous supply of heat and power from a single system).
• Mathematical models of DNA methylation dynamics: Implications for health and ageing.

(2018-11-15)
DNA methylation is a key epigenetic process which has been intimately associated with gene regulation. In recent years growing evidence has associated DNA methylation status with a variety of diseases including cancer, Alzheimer's disease and cardiovascular disease. Moreover, changes to DNA methylation have also recently been implicated in the ageing process. The factors which underpin DNA methylation are complex, and remain to be fully elucidated. Over the years mathematical modelling has helped to shed light on the dynamics of this important molecular system. Although the existing models have contributed significantly to our overall understanding of DNA methylation, they fall short of fully capturing the dynamics of this process. In this paper we develop a linear and nonlinear model which captures more fully the dynamics of the key intracellular events which characterise DNA methylation. In particular the outcomes of our linear model result in gene promoter specific methylation levels which are more biologically plausible than those revealed by previous mathematical models. In addition, our nonlinear model predicts DNA methylation promoter bistability which is commonly observed experimentally. The findings from our models have implications for our current understanding of how changes to the dynamics which underpin DNA methylation affect ageing and health. We also propose how our ideas can be tested in the lab. [Abstract copyright: Copyright © 2018 Elsevier Ltd. All rights reserved.]
• In-depth synthetic, physicochemical and in vitro biological investigation of a new ternary V(IV) antioxidant material based on curcumin.

(Elsevier, 2018-11-06)
Curcumin is a natural product with a broad spectrum of beneficial properties relating to pharmaceutical applications, extending from traditional remedies to modern cosmetics. The biological activity of such pigments, however, is limited by their solubility and bioavailability, thereby necessitating new ways of achieving optimal tissue cellular response and efficacy as drugs. Metal ion complexation provides a significant route toward improvement of curcumin stability and biological activity, with vanadium being a representative such metal ion, amply encountered in biological systems and exhibiting exogenous bioactivity through potential pharmaceuticals. Driven by the need to optimally increase curcumin bioavailability and bioactivity through complexation, synthetic efforts were launched to seek out stable species, ultimately leading to the synthesis and isolation of a new ternary V(IV)-curcumin-(2,2’-bipyridine) complex. Physicochemical characterization (elemental analysis, FT-IR, Thermogravimetry (TGA), UV-Visible, NMR, ESI-MS, Fluorescence, X-rays) portrayed the solid-state and solution properties of the ternary complex. Pulsed-EPR spectroscopy, in frozen solutions, suggested the presence of two species, cis- and trans-conformers. Density Functional Theory (DFT) calculations revealed the salient features and energetics of the two conformers, thereby complementing EPR spectroscopy. The well-described profile of the vanadium species led to its in vitro biological investigation involving toxicity, cell metabolism inhibition in S. cerevisiae cultures, Reactive Oxygen Species (ROS)-suppressing capacity, lipid peroxidation, and plasmid DNA degradation. A multitude of bio-assays and methodologies, in comparison to free curcumin, showed that it exhibits its antioxidant potential in a concentration-dependent fashion, thereby formulating a bioreactivity profile supporting development of new efficient vanado-pharmaceuticals, targeting (extra)intra-cellular processes under (patho)physiological conditions.
• Evaluating current practice and proposing a system to enhance knowledge assets within a small software development unit

(IEEE, 2018-06-25)
Knowledge management and knowledge transfer within organisations challenge continuity and resilience in the face of changing environments. While issues are principally addressed within large organisations, there is scope to evaluate how knowledge assets are managed within small and medium enterprises and to consider how the process might be enhanced. The research reported here aimed to evaluate practice within an evolving software development unit to understand how knowledge has been acquired and utilised to further organisational development. In-depth interviews were carried out with members of the unit to elicit an understanding of individual and collective learning. Qualitative analysis of the data revealed key changes in thinking and practice as well as insight into the development of individuals' contextual knowledge and tacit understanding. This analysis led to the proposal of a bespoke, lightweight web-based system to support knowledge capture and organisational learning. This work is still in progress but it is anticipated that the results will provide a potentially novel and beneficial method for enhancing knowledge assets in small enterprises and consolidating valuable, and potentially scarce, expertise.
• Theoretical and numerical analysis of unsteady fractional viscoelastic flows in simple geometries.

(Elsevier, 2018-07-12)
In this work we discuss the connection between classical and fractional viscoelastic Maxwell models, presenting the basic theory supporting these constitutive equations, and establishing some background on the admissibility of the fractional Maxwell model. We then develop a numerical method for the solution of two coupled fractional differential equations (one for the velocity and the other for the stress), that appear in the pure tangential annular ow of fractional viscoelastic fluids. The numerical method is based on finite differences, with the approximation of fractional derivatives of the velocity and stress being inspired by the method proposed by Sun and Wu for the fractional diffusion-wave equation [ Z.Z. Sun, X. Wu, A fully discrete difference scheme for a diffusion-wave system, Applied Numerical Mathematics 56 (2006) 193-209]. We prove solvability, study numerical convergence of the method, and also discuss the applicability of this method for simulating the rheological response of complex fluids in a real concentric cylinder rheometer. By imposing a torsional step-strain, we observe the different rates of stress relaxation obtained with different values of \alpha and \beta (the fractional order exponents that regulate the viscoelastic response of the complex fluids).
• Magnetron Sputter-Coated Nanoparticle MoS2 Supported on Nanocarbon: A Highly Efficient Electrocatalyst toward the Hydrogen Evolution Reaction

(American Chemical Society, 2018-07-03)
The design and fabrication of inexpensive highly efficient electrocatalysts for the production of hydrogen via the hydrogen evolution reaction (HER) underpin a plethora of emerging clean energy technologies. Herein, we report the fabrication of highly efficient electrocatalysts for the HER based on magnetron-sputtered MoS2 onto a nanocarbon support, termed MoS2/C. Magnetron sputtering time is explored as a function of its physiochemical composition and HER performance; increased sputtering times give rise to materials with differing compositions, i.e., Mo4+ to Mo6+ and associated S anions (sulfide, elemental, and sulfate), and improved HER outputs. An optimized sputtering time of 45 min was used to fabricate the MoS2/C material. This gave rise to an optimal HER performance with regard to its HER onset potential, achievable current, and Tafel value, which were −0.44 (vs saturated calomel electrode (SCE)), −1.45 mV s−1, and 43 mV dec−1, respectively, which has the highest composition of Mo4+ and sulfide (MoS2). Electrochemical testing toward the HER via drop casting MoS2/C upon screen-printed electrodes (SPEs) to electrically wire the nanomaterial is found to be mass coverage dependent, where the current density increases up to a critical mass (ca. 50 μg cm−2), after which a plateau is observed. To allow for a translation of the bespoke fabricated MoS2/C from laboratory to new industrial applications, MoS2/C was incorporated into the bulk ink utilized in the fabrication of SPEs (denoted as MoS2/C-SPE), thus allowing for improved electrical wiring to the MoS2/C and resulting in the production of scalable and reproducible electrocatalytic platforms. The MoS2/C-SPEs displayed far greater HER catalysis with a 450 mV reduction in the HER onset potential and a 1.70 mA cm−2 increase in the achievable current density (recorded at −0.75 V (vs SCE)), compared to a bare/unmodified graphitic SPE. The approach of using magnetron sputtering to modify carbon with MoS2 facilitates the production of mass-producible, stable, and effective electrode materials for possible use in electrolyzers, which are cost competitive to Pt and mitigate the need to use time-consuming and low-yield exfoliation techniques typically used to fabricate pristine MoS2.