Mechanism of the thermal decomposition of bisphenol C polycarbonate: nature of its fire resistance

Quantum chemical methods have been used to identify reaction pathways of the thermal decomposition of bisphenol C polycarbonate, one of the most fire-resistant polymers known to the scientific community. Despite substantial interest in its unusual high-temperature behavior, the mechanism of its thermal decomposition has been unknown. On the basis of computational results, a mechanism is proposed where the main feature is a shift of Cl atom from the β-styrene position to the adjacent aromatic ring, which leads to crosslinking and cyclization of the polymer. The proposed mechanism is consistent with experimental observations of char, HCl, and CO₂ as the main pyrolysis products.     

Inorganic Protection of Polymer Nanocapsules: A Strategy to Improve the Efficiency of Encapsulated Optically Active Molecules

We demonstrate that the efficiency under ambient conditions of optically active molecules encapsulated in polymer nanocapsules can be significantly improved by depositing an inorganic layer onto the polymeric shell. A triplet-triplet annihilation upconversion (TTA-UC) system consisting of a porphyrin derivative and perylene is used as a representative case. Different inorganic materials are deposited on the surface of functionalized polymer nanocapsules synthesized by free-radical polymerization in miniemulsion. First, a silicate clay with formula [Si₈(Mg_5.45Li_0.4)O₂₀(OH)₄]Na_0.7 is deposited on the surface of positively charged polystyrene nanocapsules via layer-by-layer deposition. Second, controlled in situ mineralization of hydroxyapatite and cerium(IV) oxide are carried out on the surface of negatively charged polystyrene nanocapsules. In both cases the inorganic materials on the nanocapsule surface act as a scavenger and avoid the entry of oxygen from the external environment. By avoiding the entry of oxygen, the photo-oxidation process of perylene molecules is avoided within the system, and an increase in the TTA-UC properties occurs.     

Charge Migration in Organic Materials: Can Propagating Charges Affect the Key Physical Quantities Controlling Their Motion?

Charge migration is a ubiquitous phenomenon with profound implications throughout many areas of chemistry, physics, biology, and materials science. The long-term vision of designing functional materials with tailored molecular-scale properties has triggered an increasing quest to identify prototypical systems where truly molecular conduction pathways play a fundamental role. Such pathways can be formed due to the molecular organization of various organic materials and are widely used to discuss electronic properties at the nanometer scale. Here, we present a computational methodology to study charge propagation in organic molecular stacks at nano and sub-nanoscales and exploit this methodology to demonstrate that moving charge carriers strongly affect the values of the physical quantities controlling their motion. The approach is also expected to find broad application in the field of charge migration in soft matter systems.     

The effects of IT-related attributional style in voluntary technology training

IT training is firmly established as a key condition that influences successful technology adoption, yet little is known about factors that can affect voluntary training participation. We evaluate the predictive value of IT-related attributional style in relation to the intention to participate in voluntary training in the context of a mandatory enterprise resource planning system rollout. We find that individual IT-related attributional style is highly predictive of the intention to participate.     

Classes of submodular constraints expressible by graph cuts

Submodular constraints play an important role both in theory and practice of valued constraint satisfaction problems (VCSPs). It has previously been shown, using results from the theory of combinatorial optimisation, that instances of VCSPs with submodular constraints can be minimised in polynomial time. However, the general algorithm is of order O(n ⁶) and hence rather impractical. In this paper, by using results from the theory of pseudo-Boolean optimisation, we identify several broad classes of submodular constraints over a Boolean domain which are expressible using binary submodular constraints, and hence can be minimised in cubic time. Furthermore, we describe how our results translate to certain optimisation problems arising in computer vision.     

Analysis of multi-agent activity using petri nets

This paper presents the use of place/transition petri nets (PNs) for the recognition and evaluation of complex multi-agent activities. The PNs were built automatically from the activity templates that are routinely used by experts to encode domain-specific knowledge. The PNs were built in such a way that they encoded the complex temporal relations between the individual activity actions. We extended the original PN formalism to handle the propagation of evidence using net tokens. The evaluation of the spatial and temporal properties of the actions was carried out using trajectory-based action detectors and probabilistic models of the action durations. The presented approach was evaluated using several examples of real basketball activities. The obtained experimental results suggest that this approach can be used to determine the type of activity that a team has performed as well as the stage at which the activity ended.     

The Network as a Storage Device: Dynamic Routing with Bounded Buffers

We study dynamic routing in store-and-forward packet networks where each network link has bounded buffer capacity for receiving incoming packets and is capable of transmitting a fixed number of packets per unit of time. At any moment in time, packets are injected at various network nodes with each packet specifying its destination node. The goal is to maximize the throughput, defined as the number of packets delivered to their destinations. In this paper, we make some progress on throughput maximization in various network topologies. Let n and m denote the number of nodes and links in the network, respectively. For line networks, we show that Nearest-to-Go (NTG), a natural distributed greedy algorithm, is -competitive, essentially matching a known lower bound on the performance of any greedy algorithm. We also show that if we allow the online routing algorithm to make centralized decisions, there is a randomized polylog(n)-competitive algorithm for line networks as well as for rooted tree networks, where each packet is destined for the root of the tree. For grid graphs, we show that NTG has a competitive ratio of while no greedy algorithm can achieve a ratio better than . Finally, for arbitrary network topologies, we show that NTG is -competitive, improving upon an earlier bound of O(mn). An extended abstract appeared in the Proceedings of the 8th Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005, Berkeley, CA, USA, pp. 1–13, Lecture Notes in Computer Science, vol. 1741, Springer, Berlin. S. Angelov is supported in part by NSF Career Award CCR-0093117, NSF Award ITR 0205456 and NIGMS Award 1-P20-GM-6912-1. S. Khanna is supported in part by an NSF Career Award CCR-0093117, NSF Award CCF-0429836, and a US-Israel Binational Science Foundation Grant. K. Kunal is supported in part by an NSF Career Award CCR-0093117 and NSF Award CCF-0429836.     

Towards interactive simulation in automotive design

One of the important tasks in Mechanical Engineering is to increase the safety of the vehicle and decrease its production costs. This task is typically solved by means of Multiobjective Optimization, which formulates the problem as a mapping from the space of design variables to the space of target criteria and tries to find an optimal region in these multidimensional spaces. Due to high computational costs of numerical simulations, the sampling of this mapping is usually very sparse and scattered. Combining design of experiments methods, metamodeling, new interpolation schemes and innovative graphics methods, we enable the user to interact with simulation parameters, optimization criteria, and come to a new interpolated crash result within seconds. We denote this approach as Simulated Reality, a new concept for the interplay between simulation, optimization and interactive visualization. In this paper we show the application of Simulated Reality for solution of real life car design optimization problems.

Robust self-assembly of graphs

Self-assembly is a process in which small building blocks interact autonomously to form larger structures. A recently studied model of self-assembly is the Accretive Graph Assembly Model whereby an edge-weighted graph is assembled one vertex at a time starting from a designated seed vertex. The weight of an edge specifies the magnitude of attraction (positive weight) or repulsion (negative weight) between adjacent vertices. It is feasible to add a vertex to the assembly if the total attraction minus repulsion of the already built neighbors exceeds a certain threshold, called the assembly temperature. This model naturally generalizes the extensively studied Tile Assembly Model. A natural question in graph self-assembly is to determine whether or not there exists a sequence of feasible vertex additions to realize the entire graph. However, even when it is feasible to realize the assembly, not much can be inferred about its likelihood of realization in practice due to the uncontrolled nature of the self-assembly process. Motivated by this, we introduce the robust self-assembly problem where the goal is to determine if every possible sequence of feasible vertex additions leads to the completion of the assembly. We show that the robust self-assembly problem is co-NP-complete even on planar graphs with two distinct edge weights. We then examine the tractability of the robust self-assembly problem on a natural subclass of planar graphs, namely grid graphs. We identify structural conditions that determine whether or not a grid graph can be robustly self-assembled, and give poly-time algorithms to determine this for several interesting cases of the problem. Finally, we also show that the problem of counting the number of feasible orderings that lead to the completion of an assembly is #P-complete.     

Fabrication of buried microfluidic channels with observation windows using femtosecond laser photoablation and parylene-C coating

We developed an advanced method for fabricating microfluidic structures comprising channels and inputs/outputs buried within a silicon wafer based on single level lithography. We etched trenches into a silicon substrate, covered these trenches with parylene-C, and selectively opened their bottoms using femtosecond laser photoablation, forming channels and inputs/outputs by isotropic etching of silicon by xenon difluoride vapors. We subsequently sealed the channels with a second parylene-C layer. Unlike in previously published works, this entire process is conducted at ambient temperature to allow for integration with complementary metal oxide semiconductor devices for smart readout electronics. We also demonstrated a method of chip cryo-cleaving with parylene presence that allows for monitoring of the process development. We also created an observation window for in situ visualization inside the opaque silicon substrate by forming a hole in the parylene layer at the silicon backside and with local silicon removal by xenon difluoride vapor etching. We verified the microfluidic chip performance by forming a segmented flow of a fluorescein solution in an oil stream. This proposed technique provides opportunities for forming simple microfluidic systems with buried channels at ambient temperature.