Spin-polarization and ferromagnetism of graphitic carbon nitride materials

Polymeric graphitic carbon nitride materials have attracted increasing attention in recent years owning to their potential applications in energy conversion, environment protection, and so on. Here, from first-principles calculations, we report the electronic structure modification of graphitic carbon nitride (g-C3N4) in response to carbon doping. We showed that each dopant atom can induce a local magnetic moment of 1.0 μB in non-magnetic g-C3N4. At the doping concentration of 1/14, the local magnetic moments of the most stable doping configuration which has the dopant atom at the center of heptazine unit prefer to align in a parallel way leading to long-range ferromagnetic (FM) ordering. When the joint N atom is replaced by C atom, the system favors an antiferromagnetic (AFM) ordering at unstrained state, but can be tuned to ferromagnetism (FM) by applying biaxial tensile strain. More interestingly, the FM state of the strained system is half-metallic with abundant states at the Fermi level in one spin channel and a band gap of 1.82 eV in another spin channel. The Curie temperature (Tc) was also evaluated using a mean-field theory and Monte Carlo simulations within the Ising model. Such tunable electron spin-polarization and ferromagnetism are quite promising for the applications of graphitic carbon nitride in spintronics.

Timing, origin and emplacement dynamics of mass flows offshore of SE Montserrat in the last 110 ka : implications for landslide and tsunami hazards, eruption history, and volcanic island evolution

Mass flows on volcanic islands generated by volcanic lava dome collapse and by larger-volume flank collapse can be highly dangerous locally and may generate tsunamis that threaten a wider area. It is therefore important to understand their frequency, emplacement dynamics, and relationship to volcanic eruption cycles. The best record of mass flow on volcanic islands may be found offshore, where most material is deposited and where intervening hemipelagic sediment aids dating. Here we analyze what is arguably the most comprehensive sediment core data set collected offshore from a volcanic island. The cores are located southeast of Montserrat, on which the Soufriere Hills volcano has been erupting since 1995. The cores provide a record of mass flow events during the last 110 thousand years. Older mass flow deposits differ significantly from those generated by the repeated lava dome collapses observed since 1995. The oldest mass flow deposit originated through collapse of the basaltic South Soufriere Hills at 103-110 ka, some 20-30 ka after eruptions formed this volcanic center. A ∼1.8 km3 blocky debris avalanche deposit that extends from a chute in the island shelf records a particularly deep-seated failure. It likely formed from a collapse of almost equal amounts of volcanic edifice and coeval carbonate shelf, emplacing a mixed bioclastic-andesitic turbidite in a complex series of stages. This study illustrates how volcanic island growth and collapse involved extensive, large-volume submarine mass flows with highly variable composition. Runout turbidites indicate that mass flows are emplaced either in multiple stages or as single events.

Optical data encryption using time-dependent dynamics of refractive index changes in LiNbO3

We present a method for optical encryption of information, based on the time-dependent dynamics of writing and erasure of refractive index changes in a bulk lithium niobate medium. Information is written into the photorefractive crystal with a spatially amplitude modulated laser beam which when overexposed significantly degrades the stored data making it unrecognizable. We show that the degradation can be reversed and that a one-to-one relationship exists between the degradation and recovery rates. It is shown that this simple relationship can be used to determine the erasure time required for decrypting the scrambled index patterns. In addition, this method could be used as a straightforward general technique for determining characteristic writing and erasure rates in photorefractive media.

Distinguishing between mean-field, moment dynamics and stochastic descriptions of birth-death-movement processes

Mathematical descriptions of birth–death–movement processes are often calibrated to measurements from cell biology experiments to quantify tissue growth rates. Here we describe and analyze a discrete model of a birth–death-movement process applied to a typical two–dimensional cell biology experiment. We present three different descriptions of the system: (i) a standard mean–field description which neglects correlation effects and clustering; (ii) a moment dynamics description which approximately incorporates correlation and clustering effects, and; (iii) averaged data from repeated discrete simulations which directly incorporates correlation and clustering effects. Comparing these three descriptions indicates that the mean–field and moment dynamics approaches are valid only for certain parameter regimes, and that both these descriptions fail to make accurate predictions of the system for sufficiently fast birth and death rates where the effects of spatial correlations and clustering are sufficiently strong. Without any method to distinguish between the parameter regimes where these three descriptions are valid, it is possible that either the mean–field or moment dynamics model could be calibrated to experimental data under inappropriate conditions, leading to errors in parameter estimation. In this work we demonstrate that a simple measurement of agent clustering and correlation, based on coordination number data, provides an indirect measure of agent correlation and clustering effects, and can therefore be used to make a distinction between the validity of the different descriptions of the birth–death–movement process.

Experiential learning as a constraint-led process: an ecological dynamics perspective

In this paper we present key ideas for an ecological dynamics approach to learning that reveal the importance of learner–environment interactions to frame outdoor experiential learning.We propose that ecological dynamics provides a useful framework for understanding the interacting constraints of the learning process and for designing learning opportunities in outdoor experiential learning.

An ecological dynamics approach to skill acquisition : implications for development of talent in sport.

This paper proposes how ecological dynamics, a theory focusing on the performer-environment relationship, provides a basis for understanding skill acquisition in sport. From this perspective, learners are conceptualized as complex, neurobiological systems in which inherent self-organisation tendencies support the emergence of adaptive behaviours under a range of interacting task and environmental constraints. Intentions, perceptions and actions are viewed as intertwined processes which underpin functional movement solutions assembled by each learner during skill acquisition. These ideas suggest that skill acquisition programmes need to sample information from the performance environment to guide behaviour in practice tasks. Skill acquisition task protocols should allow performers to use movement variability to explore and create opportunities for action, rather than constraining them to passively receiving information. This conceptualisation also needs to characterize the design of talent evaluation tests, which need to faithfully represent the perception-action relationships in the performance environment. Since the dynamic nature of changing task constraints in sports cannot be predicted over longer timescales, an implication is that talent programmes should focus on developing performance expertise in each individual, rather than over-relying on identification of expert performers at specific points in time.

Control of infrastructure inspection aircraft vertical dynamics in the presence of thermal disturbances

The low-altitude aircraft inspection of powerlines, or other linear infrastructure networks, is emerging as an important application requiring specialised control technologies. Despite some recent advances in automated control related to this application, control of the underactuated aircraft vertical dynamics has not been completely achieved, especially in the presence of thermal disturbances. Rejection of thermal disturbances represents a key challenge to the control of inspection aircraft due to the underactuated nature of the dynamics and specified speed, altitude, and pitch constraints. This paper proposes a new vertical controller consisting of a backstepping elevator controller with feedforward-feedback throttle controller. The performance of our proposed approach is evaluated against two existing candidate controllers.

City relative price dynamics in Australia : are structural breaks important?

This paper examines the dynamic behaviour of relative prices across seven Australian cities by applying panel unit root test procedures with structural breaks to quarterly consumer price index data for 1972 Q1–2011 Q4. We find overwhelming evidence of convergence in city relative prices. Three common structural breaks are endogenously determined at 1985, 1995, and 2007. Further, correcting for two potential biases, namely Nickell bias and time aggregation bias, we obtain half-life estimates of 2.3–3.8 quarters that are much shorter than those reported by previous research. Thus, we conclude that both structural breaks and bias corrections are important to obtain shorter half-life estimates.

Structural dynamics education in the new millennium

Structural Dynamics is the study of the response of structures to dynamic or time varying loads. This topic has emerged to be one of importance to all structural engineers due to three important issues with structural engineering in the new millennium. These are: (1) vibration and problems in slender structures that have emerged due to new material technology and aesthetic requirements, (ii) ageing structures such as bridges whoese health needs to be monitored and appropriate retrofitting carried out to prevent failure and (iii) increased vulnerability of structures to random loads such as seismic, impact and blast loads. Knowledge of structural dynamics is necessary to address these issues and their consequences. During the past two decades, research in structural dynamics has generated considerable amount of new information to address these issues. This new knowledge is not readily made available to practicing engineers and very little or none of it enters the classrooms. There is no universal emphasis on including structural dynamics and their recently generated new knowledge into the civil/structural curriculum. This paper argues for the need to include structural dynamics into the syllabus of all civil engineering courses especially those having a first or second major in structural engineering. This will enable our future structural engineers to design and maintain safe and efficient structures.

Correlating flow induced shear stress and chondrocytes activity in micro-porous scaffold using computational fluid dynamics and rapid prototyping

Flow induced shear stress plays an important role in regulating cell growth and distribution in scaffolds. This study sought to correlate wall shear stress and chondrocytes activity for engineering design of micro-porous osteochondral grafts based on the hypothesis that it is possible to capture and discriminate between the transmitted force and cell response at the inner irregularities. Unlike common tissue engineering therapies with perfusion bioreactors in which flow-mediated stress is the controlling parameter, this work assigned the associated stress as a function of porosity to influence in vitro proliferation of chondrocytes. D-optimality criterion was used to accommodate three pore characteristics for appraisal in a mixed level fractional design of experiment (DOE); namely, pore size (4 levels), distribution pattern (2 levels) and density (3 levels). Micro-porous scaffolds (n=12) were fabricated according to the DOE using rapid prototyping of an acrylic-based bio-photopolymer. Computational fluid dynamics (CFD) models were created correspondingly and used on an idealized boundary condition with a Newtonian fluid domain to simulate the dynamic microenvironment inside the pores. In vitro condition was reproduced for the 3D printed constructs seeded by high pellet densities of human chondrocytes and cultured for 72 hours. The results showed that cell proliferation was significantly different in the constructs (p<0.05). Inlet fluid velocity of 3×10-2mms-1 and average shear stress of 5.65×10-2 Pa corresponded with increased cell proliferation for scaffolds with smaller pores in hexagonal pattern and lower densities. Although the analytical solution of a Poiseuille flow inside the pores was found insufficient for the description of the flow profile probably due to the outside flow induced turbulence, it showed that the shear stress would increase with cell growth and decrease with pore size. This correlation demonstrated the basis for determining the relation between the induced stress and chondrocyte activity to optimize microfabrication of engineered cartilaginous constructs.

Locally weighted learning model predictive control for nonlinear and time varying dynamics

This paper proposes an online learning control system that uses the strategy of Model Predictive Control (MPC) in a model based locally weighted learning framework. The new approach, named Locally Weighted Learning Model Predictive Control (LWL-MPC), is proposed as a solution to learn to control robotic systems with nonlinear and time varying dynamics. This paper demonstrates the capability of LWL-MPC to perform online learning while controlling the joint trajectories of a low cost, three degree of freedom elastic joint robot. The learning performance is investigated in both an initial learning phase, and when the system dynamics change due to a heavy object added to the tool point. The experiment on the real elastic joint robot is presented and LWL-MPC is shown to successfully learn to control the system with and without the object. The results highlight the capability of the learning control system to accommodate the lack of mechanical consistency and linearity in a low cost robot arm.

Molecular dynamics investigation on shearing between osteopontin and hydroxyapatite in biological materials

Bone, a hard biological material, possesses a combination of high stiffness and toughness, even though the main basic building blocks of bone are simply mineral platelets and protein molecules. Bone has a very complex microstructure with at least seven hierachical levels. This unique material characteristic attracts great attention, but the deformation mechanisms in bone have not been well understood. Simulation at nano-length scale such as molecular dynamics (MD) is proven to be a powerful tool to investigate bone nanomechanics for developing new artificial biological materials. This study focuses on the ultra large and thin layer of extrafibrillar protein matrix (thickness = ~ 1 nm) located between mineralized collagen fibrils (MCF). Non-collagenous proteins such as osteopontin (OPN) can be found in this protein matrix, while MCF consists mainly of hydroxyapatite (HA) nanoplatelets (thickness = 1.5 – 4.5 nm). By using molecular dynamics method, an OPN peptide was pulled between two HA mineral platelets with water in presence. Periodic boundary condition (PBC) was applied. The results indicate that the mechanical response of OPN peptide greatly depends on the attractive electrostatics interaction between the acidic residues in OPN peptide and HA mineral surfaces. These bonds restrict the movement of OPN peptide, leading to a high energy dissipation under shear loading.

Spin-coated carbon

We describe a novel and facile approach to covalently graft molecules containing stable free radicals onto carbon surfaces including graphene, carbon nanotubes, glassy carbon and carbon fibres. The new technique employs a stable aryl nitroxide radical diazonium tetrafluoroborate salt. The salt may be isolated and added to carbon surfaces in solution, suspension or electrochemically and represents a convenient, versatile and highly efficient means to adorn graphitic materials with large numbers of free radical spin systems

Tensile properties of graphene nanotube hybrid structures : a molecular dynamics study

Graphene has been reported with record-breaking properties which have opened up huge potential applications. A considerable research has been devoted to manipulate or modify the properties of graphene to target a more smart nanoscale device. Graphene and carbon nanotube hybrid structure (GNHS) is one of the promising graphene derivates, while their mechanical properties have been rarely discussed in literature. Therefore, such a studied is conducted in this paper basing on the large-scale molecular dynamics simulation. The target GNHS is constructed by considering two separate graphene layers that being connected by single-wall carbon nanotubes (SWCNTs) according to the experimental observations. It is found that the GNHSs exhibit a much lower yield strength, Young’s modulus, and earlier yielding comparing with a bilayer graphene sheet. Fracture of studied GNHSs is found to fracture located at the connecting region between carbon nanotubes (CNTs) and graphene. After failure, monatomic chains are normally observed at the front of the failure region, and the two graphene layers at the failure region without connecting CNTs will adhere to each other, generating a bilayer graphene sheet scheme (with a layer distance about 3.4 Å). This study will enrich the current understanding of the mechanical performance of GNHS, which will guide the design of GNHS and shed lights on its various applications.