Kinetics of sono-photooxidative degradation of poly(alkyl methacrylate)s

The mechano-chemical degradation of poly(methyl methacrylate) (PMMA), poly(ethyl methacrylate) (PEMA) and poly(n-butyl methacrylate) (PBMA) using ultrasound (US), ultraviolet (UV) radiation and a photoinitiator (benzoin) has been investigated. The degradation of the polymers was monitored using the reduction in number average molecular weight (M-n) and polydispersity (PDI). A degradation mechanism that included the decomposition of the initiator, generation of polymer radicals by the hydrogen abstraction of initiator radicals, reversible chain transfer between stable polymer and polymer radicals was proposed. The mechanism assumed mid-point chain scission due to US and random scission due to UV radiation. A series of experiments with different initial M-n of the polymers were performed and the results indicated that, irrespective of the initial PDI, the PDI during the sono-photooxidative degradation evolved to a steady state value of 1.6 +/- 0.05 for all the polymers. This steady state evolution of PDI was successfully predicted by the continuous distribution kinetics model. The rate coefficients of polymer scission due to US and UV exhibited a linear increase and decrease with the size of the alkyl group of the poly(alkyl methacrylate)s, respectively. (C) 2010 Elsevier B.V. All rights reserved.

Catalytic oxidative polymerization of 1,1-diphenylethylene at ambient temperature and potential application of peroxide macroinitiator

The Co(II)TPP(Py) complex was used as an efficient dioxygen carrier for the radical polymerization of 1,1-diphenylethylene (DPE), which has a low ceiling temperature, at ambient temperature and low oxygen pressure. The mechanism of polymerization is discussed' on the basis of kinetic data, W-vis, ESR, and H-1 NMR studies. The rate of polymerization (RP) and number-average molecular weights (M) of poly(1,1-diphenylethylene peroxide) (PDPEP) are higher and the polydispersity is lower than in 2,2'-azobis(isobutyronitrile) (AIBN) initiated polymerization. PDPEP was further. used as a macroinitiator for the polymerization of MMA. The polymerization obeys classical kinetics. The K-2 value of the PDPEP has been determined from the slope of R-P(2) VS [M](2)[I], which reveals that it can also be used at higher temperature for the polymerization. An "active" PMMA was also synthesized, containing initiating segments in the polymer backbone.

SEC-MALDI-TOF mass spectral characterization of a hyperbranched polyether prepared via melt transetherification

An AB(2) monomer, 1-(2-hydroxyethoxy)-3,5-bis-(methoxymethyl)-2,4,6-trimethylbenzene, was synthesized from mesitol and melt-polycondensed in the presence of an acid catalyst via a transetherification process at 145-150 degreesC to yield a soluble, moderately high molecular weight hyperbranched polyether. The degree of branching in the polymer was calculated to be 0.78 by a comparison of its NMR spectrum with that of an appropriately designed model compound. The weight-average molecular weight of the hyperbranched polymer was determined to be 64,600 (weight-average molecular weight/number-average molecular weight = 5.2) by size exclusion chromatography (SEC) in CHCl3, with polystyrene standards. The origin of the broad molecular weight distribution, which could either be intrinsic to such hyperbranched structures or be due to structural heterogeneity, was further probed by the fractionation of the samples by SEC and by the subjection of each fraction to matrix-assisted laser desorption/ionization time-of-flight mass spectral analysis. The mass spectral analysis suggested the presence of two primary types of species: one corresponding to the simple branched structure and the other to macrocyclics. Interestingly, from the relative intensities of the two peaks, it was apparent that cyclization became favorable at higher conversions in the melt transetherification process. (C) 2002 Wiley Periodicals, Inc.

On the Average Case Communication Complexity for Detection in Sensor Networks

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space viewpoint is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces $\mathcal{S_I}$ and $\mathcal{S_C}$ and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating $\mathcal{S_I}$ and $\mathcal{S_C}$ is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. The average case CC of the relevant greater-than (GT) function is characterized within two bits. In the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm.

Fault-Tolerant Average Execution Time Optimization for General Purpose Multi-Processor System-on Chips

Fault-tolerance is due to the semiconductor technology development important, not only for safety-critical systems but also for general-purpose (non-safety critical) systems. However, instead of guaranteeing that deadlines always are met, it is for general-purpose systems important to minimize the average execution time (AET) while ensuring fault-tolerance. For a given job and a soft (transient) error probability, we define mathematical formulas for AET that includes bus communication overhead for both voting (active replication) and rollback-recovery with checkpointing (RRC). And, for a given multi-processor system-on-chip (MPSoC), we define integer linear programming (ILP) models that minimize AET including bus communication overhead when: (1) selecting the number of checkpoints when using RRC, (2) finding the number of processors and job-to-processor assignment when using voting, and (3) defining fault-tolerance scheme (voting or RRC) per job and defining its usage for each job. Experiments demonstrate significant savings in AET.

Cubicity, degeneracy, and crossing number

A $k$-box $B=(R_1,...,R_k)$, where each $R_i$ is a closed interval on the real line, is defined to be the Cartesian product $R_1\times R_2\times ...\times R_k$. If each $R_i$ is a unit length interval, we call $B$ a $k$-cube. Boxicity of a graph $G$, denoted as $\boxi(G)$, is the minimum integer $k$ such that $G$ is an intersection graph of $k$-boxes. Similarly, the cubicity of $G$, denoted as $\cubi(G)$, is the minimum integer $k$ such that $G$ is an intersection graph of $k$-cubes. It was shown in [L. Sunil Chandran, Mathew C. Francis, and Naveen Sivadasan: Representing graphs as the intersection of axis-parallel cubes. MCDES-2008, IISc Centenary Conference, available at CoRR, abs/cs/ 0607092, 2006.] that, for a graph $G$ with maximum degree $\Delta$, $\cubi(G)\leq \lceil 4(\Delta +1)\log n\rceil$. In this paper, we show that, for a $k$-degenerate graph $G$, $\cubi(G) \leq (k+2) \lceil 2e \log n \rceil$. Since $k$ is at most $\Delta$ and can be much lower, this clearly is a stronger result. This bound is tight. We also give an efficient deterministic algorithm that runs in $O(n^2k)$ time to output a $8k(\lceil 2.42 \log n\rceil + 1)$ dimensional cube representation for $G$. An important consequence of the above result is that if the crossing number of a graph $G$ is $t$, then $\boxi(G)$ is $O(t^{1/4}{\lceil\log t\rceil}^{3/4})$ . This bound is tight up to a factor of $O((\log t)^{1/4})$. We also show that, if $G$ has $n$ vertices, then $\cubi(G)$ is $O(\log n + t^{1/4}\log t)$. Using our bound for the cubicity of $k$-degenerate graphs we show that cubicity of almost all graphs in $\mathcal{G}(n,m)$ model is $O(d_{av}\log n)$, where $d_{av}$ denotes the average degree of the graph under consideration. model is O(davlogn).

Tradeoff of average power and average delay for a point-to-point link with fading

We consider a discrete time system with packets arriving randomly at rate lambda per slot to a fading point-to-point link, for which the transmitter can control the number of packets served in a slot by varying the transmit power. We provide an asymptotic characterization of the minimum average delay of the packets, when average transmitter power is a small positive quantity V more than the minimum average power required for queue stability. We show that the minimum average delay will grow either as log (1/V) or 1/V when V down arrow 0, for certain sets of values of lambda. These sets are determined by the distribution of fading gain, the maximum number of packets which can be transmitted in a slot, and the assumed transmit power function, as a function of the fading gain and the number of packets transmitted. We identify a case where the above behaviour of the tradeoff differs from that obtained from a previously considered model, in which the random queue length process is assumed to evolve on the non-negative real line.

Optimal design of timer-based, distributed selection with unknown number of nodes

The timer-based selection scheme is a popular, simple, and distributed scheme that is used to select the best node from a set of available nodes. In it, each node sets a timer as a function of a local preference number called a metric, and transmits a packet when its timer expires. The scheme ensures that the timer of the best node, which has the highest metric, expires first. However, it fails to select the best node if another node transmits a packet within Delta s of the transmission by the best node. We derive the optimal timer mapping that maximizes the average success probability for the practical scenario in which the number of nodes in the system is unknown but only its probability distribution is known. We show that it has a special discrete structure, and present a recursive characterization to determine it. We benchmark its performance with ad hoc approaches proposed in the literature, and show that it delivers significant gains. New insights about the optimality of some ad hoc approaches are also developed.

Optimal Timer-Based Best Node Selection for Wireless Systems with Unknown Number of Nodes

The distributed, low-feedback, timer scheme is used in several wireless systems to select the best node from the available nodes. In it, each node sets a timer as a function of a local preference number called a metric, and transmits a packet when its timer expires. The scheme ensures that the timer of the best node, which has the highest metric, expires first. However, it fails to select the best node if another node transmits a packet within Delta s of the transmission by the best node. We derive the optimal metric-to-timer mappings for the practical scenario where the number of nodes is unknown. We consider two cases in which the probability distribution of the number of nodes is either known a priori or is unknown. In the first case, the optimal mapping maximizes the success probability averaged over the probability distribution. In the second case, a robust mapping maximizes the worst case average success probability over all possible probability distributions on the number of nodes. Results reveal that the proposed mappings deliver significant gains compared to the mappings considered in the literature.

Impact dynamics of high Weber number drops on chemically modified metallic surfaces

Hydrophobic/superhydrophobic metallic surfaces prepared via chemical treatment are encountered in many industrial scenarios involving the impingement of spray droplets. The effectiveness of such surfaces is understood through the analysis of droplet impact experiments. In the present study, three target surfaces with aluminum (Al-6061) as base material-acid-etched, Octadecyl Trichloro Silane (OTS) coated, and acid-etched plus OTS-coated-were prepared. Experiments on the impact of inertia dominated water drops on these chemically modified aluminum surfaces were carried out with the objective to highlight the effect of chemical treatment on the target surfaces on key sub-processes occurring in drop impact phenomenon. High speed videos of the entire drop impact dynamics were captured at three Weber number (We) conditions representative of high We (We > 200) regime. During the early stages of drop spreading, the drop impact resulted in ejection of secondary droplets from spreading drop front on the etched surfaces resembling prompt splash on rough surfaces whereas no such splashing was observable on untreated aluminum surface. Prominent development of undulations (fingers) were observed at the rim of drop spreading on the etched surfaces; between the etched surfaces the OTS-coated surface showed a subdued development of fingers than the uncoated surface. The impacted drops showed intense receding on OTS-coated surfaces whereas on the etched surface a highly irregular receding, with drop liquid sticking to the surface, was observed. Quantitative analyses were performed to reveal the effect of target surface characteristics on drop impact parameters such as temporal variation of spread factor of drop lamella, temporal variation of average finger length during spreading phase, maximum drop spreading, time taken to attain maximum spreading, sensitivity of maximum spreading to We, number of fingers at maximum spreading, and average receding velocity of drop lamella. Existing models for maximum drop spreading showed reasonably good agreement with the experimental measurements on the target surfaces except the acid-etched surface. (C) 2014 Elsevier B.V. All rights reserved.

Average Overlap for Clustering Incomplete Data using Symmetric Non-Negative Matrix Factorization

Clustering techniques which can handle incomplete data have become increasingly important due to varied applications in marketing research, medical diagnosis and survey data analysis. Existing techniques cope up with missing values either by using data modification/imputation or by partial distance computation, often unreliable depending on the number of features available. In this paper, we propose a novel approach for clustering data with missing values, which performs the task by Symmetric Non-Negative Matrix Factorization (SNMF) of a complete pair-wise similarity matrix, computed from the given incomplete data. To accomplish this, we define a novel similarity measure based on Average Overlap similarity metric which can effectively handle missing values without modification of data. Further, the similarity measure is more reliable than partial distances and inherently possesses the properties required to perform SNMF. The experimental evaluation on real world datasets demonstrates that the proposed approach is efficient, scalable and shows significantly better performance compared to the existing techniques.

Correlation equations for average deposition rate coefficients of nanoparticles in a cylindrical pore

Nanoparticle deposition behavior observed at the Darcy scale represents an average of the processes occurring at the pore scale. Hence, the effect of various pore-scale parameters on nanoparticle deposition can be understood by studying nanoparticle transport at pore scale and upscaling the results to the Darcy scale. In this work, correlation equations for the deposition rate coefficients of nanoparticles in a cylindrical pore are developed as a function of nine pore-scale parameters: the pore radius, nanoparticle radius, mean flow velocity, solution ionic strength, viscosity, temperature, solution dielectric constant, and nanoparticle and collector surface potentials. Based on dominant processes, the pore space is divided into three different regions, namely, bulk, diffusion, and potential regions. Advection-diffusion equations for nanoparticle transport are prescribed for the bulk and diffusion regions, while the interaction between the diffusion and potential regions is included as a boundary condition. This interaction is modeled as a first-order reversible kinetic adsorption. The expressions for the mass transfer rate coefficients between the diffusion and the potential regions are derived in terms of the interaction energy profile. Among other effects, we account for nanoparticle-collector interaction forces on nanoparticle deposition. The resulting equations are solved numerically for a range of values of pore-scale parameters. The nanoparticle concentration profile obtained for the cylindrical pore is averaged over a moving averaging volume within the pore in order to get the 1-D concentration field. The latter is fitted to the 1-D advection-dispersion equation with an equilibrium or kinetic adsorption model to determine the values of the average deposition rate coefficients. In this study, pore-scale simulations are performed for three values of Peclet number, Pe = 0.05, 5, and 50. We find that under unfavorable conditions, the nanoparticle deposition at pore scale is best described by an equilibrium model at low Peclet numbers (Pe = 0.05) and by a kinetic model at high Peclet numbers (Pe = 50). But, at an intermediate Pe (e.g., near Pe = 5), both equilibrium and kinetic models fit the 1-D concentration field. Correlation equations for the pore-averaged nanoparticle deposition rate coefficients under unfavorable conditions are derived by performing a multiple-linear regression analysis between the estimated deposition rate coefficients for a single pore and various pore-scale parameters. The correlation equations, which follow a power law relation with nine pore-scale parameters, are found to be consistent with the column-scale and pore-scale experimental results, and qualitatively agree with the colloid filtration theory. These equations can be incorporated into pore network models to study the effect of pore-scale parameters on nanoparticle deposition at larger length scales such as Darcy scale.

Diamond-Graphite Hybrids And The Nature Of Amorphous-Carbon And Diamond-Like Carbon

The nature of amorphous carbon has been explored by molecular mechanics by examining the structures of species such as C84Hx and C150Hx, wherein the percentage of sp(3) carbons is progressively increased in a graphitic network. The nature of diamond-like carbon has been similarly investigated by examining the structures of C84Hx and C102Hx where the percentage of sp(2) carbons is varied in an sp(3) network. The dependence of the average coordination number as well as the sp(3)/sp(2) atom ratio on the atom fraction of hydrogen has been investigated in light of the random covalent network model.

Orientational relaxation in a random dipolar lattice: Wave-number and frequency dependence

In order to understand the role of translational modes in the orientational relaxation in dense dipolar liquids, we have carried out a computer ''experiment'' where a random dipolar lattice was generated by quenching only the translational motion of the molecules of an equilibrated dipolar liquid. The lattice so generated was orientationally disordered and positionally random. The detailed study of orientational relaxation in this random dipolar lattice revealed interesting differences from those of the corresponding dipolar liquid. In particular, we found that the relaxation of the collective orientational correlation functions at the intermediate wave numbers was markedly slower at the long times for the random lattice than that of the liquid. This verified the important role of the translational modes in this regime, as predicted recently by the molecular theories. The single-particle orientational correlation functions of the random lattice also decayed significantly slowly at long times, compared to those of the dipolar liquid.

The nature of the charge-ordered state in Y0.5Ca0.5MnO3 with a very small average radius of the A-site cations

A detailed investigation of Y0.5Ca0.5MnO3 with a very small radius of the A-site cations ([r(A)] approximate to 1.13 Angstrom reveals the occurrence of a charge-ordering transition in the paramagnetic state, at a relatively high temperature of 260 K. The orthorhombic lattice distortion, as measured by the dimensionless index D, is large (similar to 1.75%) over the entire 300-100 K range, but the antiferromagnetic interactions become prominent only at low temperatures (< 160 K). The charge-ordering gap in Y0.5Ca0.5MnO3, measured by low-temperature vacuum tunnelling spectroscopy, is large (similar to 0.5 eV) and the charge-ordered state is unaffected by the application of a magnetic field of 6 T. The study indicates that the nature of charge-ordering in Y0.5Ca0.5MnO3 which is dominated by the cooperative Jahn-Teller effect and the associated lattice distortion is distinctly different from analogous manganates with larger [r(A)].