Microscopic Frictional Response of Sodium Oleate Self-Assembled on Steel

The article peruses the frictional response of an important metal working lubricant additive, sodium oleate. Frictional force microscopy is used to track the response of molecules self-assembled on a steel substrate of 3–4 nm roughness at 0% relative humidity. The friction-normal load characteristic emerges as bell-shaped, where the peak friction and normal load at peak friction are both sensitive to substrate roughness. The frictional response at loads lower than that associated with the peak friction is path reversible while at higher loads the loading and unloading paths are different. We suggest that a new low-friction interface material is created when the normal loads are high.

Self-Assembly of a Nanoscopic Prism via a New Organometallic Pt3 Acceptor and Its Fluorescent Detection of Nitroaromatics

A nanoscale-sized cage with a trigonal prismatic shape is prepared by coordination-driven self-assembly of a predesigned organometallic Pt-3 acceptor with an organic clip-type ligand. This trigonal prism is fluorescent and undergoes efficient fluorescence quenching by nitroaromatics, which are the chemical signatures of many explosives.

Self-interrupted regenerative metal cutting in turning

A new approach is used to study the global dynamics of regenerative metal cutting in turning. The cut surface is modeled using a partial differential equation (PDE) coupled, via boundary conditions, to an ordinary differential equation (ODE) modeling the dynamics of the cutting tool. This approach automatically incorporates the multiple-regenerative effects accompanying self-interrupted cutting. Taylor's 3/4 power law model for the cutting force is adopted. Lower dimensional ODE approximations are obtained for the combined tool–workpiece model using Galerkin projections, and a bifurcation diagram computed. The unstable solution branch off the subcritical Hopf bifurcation meets the stable branch involving self-interrupted dynamics in a turning point bifurcation. The tool displacement at that turning point is estimated, which helps identify cutting parameter ranges where loss of stability leads to much larger self-interrupted motions than in some other ranges. Numerical bounds are also obtained on the parameter values which guarantee global stability of steady-state cutting, i.e., parameter values for which there exist neither unstable periodic motions nor self-interrupted motions about the stable equilibrium.

Self-assembly of a nanoscopic platinum(II) double square cage

Self-assembly of a rigid tripyridyl linker with a bidentate 90 degrees Pt(II) acceptor yielded a somewhat unusual double square cage, representing the first example of Pt(II) cage of such shape. Multinuclear NMR as well as single-crystal structure analysis characterized the cage.

Self-acylation properties of type II fatty acid biosynthesis acyl carrier protein

Acyl carrier protein (ACIP) plays a central role in many metabolic processes inside the cell, and almost 4% of the total enzymes inside the cell require it as a cofactor. Here, we report self-acylation properties in ACPs from Plasmodium falciparum and Brassica napus that are essential components of type II fatty acid biosynthesis (FAS II), disproving the existing notion that this phenomenon is restricted only to ACPs involved in polyketide biosynthesis. We also provide strong evidence to suggest that catalytic self-acylation is intrinsic to the individual ACP. Mutational analysis of these ACPs revealed the key residue(s) involved in this phenomenon. We also demonstrate that these FAS 11 ACPs exhibit a high degree of selectivity for self-acylation employing only dicarboxylic acids as substrates. A plausible mechanism for the self-acylation reaction is also proposed.

Self-assembly of a nanoscopic platinum(II) double square cage

Self-assembly of a rigid tripyridyl linker with a bidentate 90 degrees Pt(II) acceptor yielded a somewhat unusual double square cage, representing the first example of Pt(II) cage of such shape. Multinuclear NMR as well as single-crystal structure analysis characterized the cage.

Multilayer single-component thin films and microcapsules via covalent bonded layer-by-layer self-assembly

Fabrication of single-component multilayer thin films still remains a challenging task via the layer-by-layer (LbL) approach. In this communication, we report the self-assembly of single-component multilayer thin films on flat and colloidal substrates through glutaraldehyde mediated covalent bonding.

Self-interrupted regenerative turning

A preliminary study of self-interrupted regenerative turning is performed in this paper. To facilitate the analysis, a new approach is proposed to model the regenerative effect in metal cutting. This model automatically incorporates the multiple-regenerative effects accompanying self-interrupted cutting. Some lower dimensional ODE approximations are obtained for this model using Galerkin projections. Using these ODE approximations, a bifurcation diagram of the regenerative turning process is obtained. It is found that the unstable branch resulting from the subcritical Hopf bifurcation meets the stable branch resulting from the self-interrupted dynamics in a turning point bifurcation. Using a rough analytical estimate of the turning point tool displacement, we can identify regions in the cutting parameter space where loss of stability leads to much greater amplitude self-interrupted motions than in some other regions.

Unraveling the packing pattern leading to gelation using SS NMR and X-ray diffraction: direct observation of the evolution of self-assembled fibers

A detailed understanding of the mode of packing patterns that leads to the gelation of low molecular mass gelators derived from bile acid esters was carried out using solid state NMR along with complementary techniques such as powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and polarizing optical microscopy (POM). Solid state C-13{H-1} cross polarization (CP) magic angle spinning (MAS) NMR of the low molecularmass gel in its native state was recorded for the first time. A close resemblance in the packing patterns of the gel, xerogel and bulk solid states was revealed upon comparing their C-13{H-1} CPMAS NMR spectral pattern. A doublet resonance pattern of C-13 signals in C-13{H-1}CPMAS NMR spectra were observed for the gelator molecules, whereas the non-gelators showed simple singlet resonance or resulted inthe formation of inclusion complexes/solvates. PXRD patterns revealed a close isomorphous nature of the gelators indicating the similarity in the mode of the packing pattern in their solid state. Direct imaging of the evolution of nanofibers (sol-gel transition) was carried out using POM, which proved the presence of self-assembled fibrillar networks (SAFINs) in the gel. Finally powder X-ray structure determination revealed the presence of two non-equivalent molecules in an asymmetric unit which is responsible for the doublet resonance pattern in the solid state NMR spectra.

A Dynamic Migration Model for Self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Self-Assembly of Biopolymers on Colloidal Particles via Hydrogen Bonding

Fabrication of multilayer microcapsules via layer-by-layer approach through hydrogen bonding has attracted enormous interest due to its strong response to pH. In this communication, we have prepared hydrogen-bonded multilayer microcapsule without using any cross-linking agent by using DNA base pair (adenine and thymine) modified biocompatible polymers. The growth of the self-assembly on colloidal (melamine formaldehyde: MF) particles has been monitored with zeta potential measurement. The capsules were obtained on dissolution of MF particles at 0.1N HCl. The capsules were characterized with scanning electron microscopy. Moreover, we have observed the salt induced microscopic change in self-assembly of this system on the surface of colloidal particles.

A Dynamic Migration Model for self-adaptive Genetic Algorithms

In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

Propagation of a spherical shock in an inhomogeneous self-gravitating or nongravitating system

The propagation of a shock wave of finite strength due to an explosion into inhomogeneous nongravitating and self-gravitating systems has been considered, using similarity principles, supposing that the density varies as an inverse power of distance from the centre of explosion. A large number of systems, characterised by different density exponents and different adiabatic coefficients of the gas have been considered for different shock strengths. The numerical integration from the shock inward has been continued to the surface of singularity where density tends to infinity and which acts like a piston in the self-gravitating case and to the surface where the velocity gradient tends to infinity in the nongravitating case. The effect of variation of shock strength, density exponent and adiabatic coefficient on the location of these singularities and on the distribution of flow parameters behind the shock has been studied. The initial energy of the system and the manner of release of the explosion energy influence strongly the flow behind the shock. The results have been graphically depicted.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.