Coordination-driven self-assembly of 2D-metallamacrocycles using a shape-selective Pt(2)(II)-organometallic 90 degrees acceptor: design, synthesis and sensing study

Synthesis of a series of two-dimensional metallamacrocycles via coordination-driven self-assembly of a shape-selective Pt(2)(II)-molecular building unit incorporating carbazole-ethynyl functionality is described. An equimolar (1 : 1) combination of a Pt(2)(II)-organometallic 90 degrees acceptor, 1, with rigid linear ditopic donors (L(a) and L(b)) afforded [4 + 4] self-assembled octanuclear molecular squares, 2 and 3, in quantitative yields, respectively [L(a) = 4,4'-bipyridine; L(b) = trans-1,2-bis(4-pyridyl)ethylene]. Conversely, a similar treatment of 1 with an amide-based unsymmetrical flexible ditopic donor, L(c), resulted in the formation of a [2 + 2] self-sorted molecular rhomboid (4a) as a single product [L(c) = N-(4-pyridyl)isonicotinamide]. Despite the possibility of several linkage isomeric macrocycles (rhomboid, triangle and square) due to the different connectivity of L(c), the formation of a single and symmetrical molecular rhomboid (4a) as the only product is an interesting observation. All the self-assembled macrocycles (2, 3 and 4a) were fully characterized by multinuclear NMR ((1)H and (31)P) and ESI-MS analysis. Further structural insights about the size and shape of the macrocycles were obtained through energy minimization using density functional theory (DFT) calculations. Decoration of the starting carbazole building unit with Pt-ethynyl functionality enriches the assemblies to be more p-electron rich and luminescent in nature. Macrocycles 2 and 3 could sense the presence of electron deficient nitroaromatics in solution by quenching of the initial intensity upon gradual addition of picric acid (PA). They exhibited the largest quenching response with high selectivity for nitroaromatics compared to several other electron deficient aromatics tested.

Methodology for Pavement Design Reliability and Back Analysis Using Markov Chain Monte Carlo Simulation

Given the increasing cost of designing and building new highway pavements, reliability analysis has become vital to ensure that a given pavement performs as expected in the field. Recognizing the importance of failure analysis to safety, reliability, performance, and economy, back analysis has been employed in various engineering applications to evaluate the inherent uncertainties of the design and analysis. The probabilistic back analysis method formulated on Bayes' theorem and solved using the Markov chain Monte Carlo simulation method with a Metropolis-Hastings algorithm has proved to be highly efficient to address this issue. It is also quite flexible and is applicable to any type of prior information. In this paper, this method has been used to back-analyze the parameters that influence the pavement life and to consider the uncertainty of the mechanistic-empirical pavement design model. The load-induced pavement structural responses (e.g., stresses, strains, and deflections) used to predict the pavement life are estimated using the response surface methodology model developed based on the results of linear elastic analysis. The failure criteria adopted for the analysis were based on the factor of safety (FOS), and the study was carried out for different sample sizes and jumping distributions to estimate the most robust posterior statistics. From the posterior statistics of the case considered, it was observed that after approximately 150 million standard axle load repetitions, the mean values of the pavement properties decrease as expected, with a significant decrease in the values of the elastic moduli of the expected layers. An analysis of the posterior statistics indicated that the parameters that contribute significantly to the pavement failure were the moduli of the base and surface layer, which is consistent with the findings from other studies. After the back analysis, the base modulus parameters show a significant decrease of 15.8% and the surface layer modulus a decrease of 3.12% in the mean value. The usefulness of the back analysis methodology is further highlighted by estimating the design parameters for specified values of the factor of safety. The analysis revealed that for the pavement section considered, a reliability of 89% and 94% can be achieved by adopting FOS values of 1.5 and 2, respectively. The methodology proposed can therefore be effectively used to identify the parameters that are critical to pavement failure in the design of pavements for specified levels of reliability. DOI: 10.1061/(ASCE)TE.1943-5436.0000455. (C) 2013 American Society of Civil Engineers.

Verification of Masonry Building Code to Flexural Behavior of Cement-Stabilized Soil Block

Most studies involving cement-stabilized soil blocks (CSSB) concern material properties, such as the characteristics of erosion and strength and how the composition of the block affects these properties. Moreover, research has been conducted on the performance of various mortars, investigating their material properties and the tensile bond strength between CSSB units and mortar. In contrast, very little is currently known about CSSB masonry structural behavior. Because structural design codes of traditional masonry buildings were well developed over the past century, many of the same principles may be applicable to CSSB masonry buildings. This paper details the topic of flexural behavior of CSSB masonry walls and whether the Masonry Standards Joint Committee (MSJC) code can be applied to this material for improved safety of such buildings. DOI: 10.1061/(ASCE)MT.1943-5533.0000566. (C) 2013 American Society of Civil Engineers.

Low embodied energy cement stabilised rammed earth building-A case study

Rammed earth is a monolithic construction and the construction process involves compaction of processed soil in progressive layers in a rigid formwork. Durable and thinner load bearing walls can be built using stabilised rammed earth. Use of inorganic additives such as cement for rammed earth walls has been in practice since the last 5-6 decades and cement stabilised rammed earth (CSRE) buildings can be seen across the world. The paper deals with the construction aspects, structural design and embodied energy analysis of a three storey load bearing school building complex. The CSRE school complex consists of 15 classrooms, an open air theatre and a service block. The complex has a built-up area of 1691.3 m(2) and was constructed employing manual construction techniques. This case study shows low embodied energy of 1.15 GJ/m(2) for the CSRE building as against 3-4 GJ/m(2) for conventional burnt clay brick load bearing masonry buildings. (C) 2013 Elsevier B.V. All rights reserved.

Evaluating FuncSION: A software for automated synthesis of design solutions for stimulating ideation during mechanical conceptual design

The goal of the work reported in this paper is to use automated, combinatorial synthesis to generate alternative solutions to be used as stimuli by designers for ideation. FuncSION, a computational synthesis tool that can automatically synthesize solution concepts for mechanical devices by combining building blocks from a library, is used for this purpose. The objectives of FuncSION are to help generate a variety of functional requirements for a given problem and a variety of concepts to fulfill these functions. A distinctive feature of FuncSION is its focus on automated generation of spatial configurations, an aspect rarely addressed by other computational synthesis programs. This paper provides an overview of FuncSION in terms of representation of design problems, representation of building blocks, and rules with which building blocks are combined to generate concepts at three levels of abstraction: topological, spatial, and physical. The paper then provides a detailed account of evaluating FuncSION for its effectiveness in providing stimuli for enhanced ideation.

Cu-II-Azide Polynuclear Complexes of Three Different Building Clusters with the Same Schiff-Base Ligand: Synthesis, Structures, Magnetic Behavior, and Density Functional Theory Studies

Three copper-azido complexes Cu-4(N-3)(8)(L-1)(2)(MeOH)(2)](n) (1), Cu-4(N-3)(8)(L-1)(2)] (2), and Cu-5(N-3)(10)(L-1)(2)](n) (3) L-1 is the imine resulting from the condensation of pyridine-2-carboxaldehyde with 2-(2-pyridyl)ethylamine] have been synthesized using lower molar equivalents of the Schiff base ligand with Cu(NO3)(2)center dot 3H(2)O and an excess of NaN3. Single crystal X-ray structures show that the basic unit of the complexes 1 and 2 contains Cu-4(II) building blocks; however, they have distinct basic and overall structures due to a small change in the bridging mode of the peripheral pair of copper atoms in the linear tetranudear structures. Interestingly, these changes are the result of changing the solvent system (MeOH/H2O to EtOH/H2O) used for the synthesis, without changing the proportions of the components (metal to ligand ratio 2:1). Using even lower proportions of the ligand, another unique complex was isolated with Cu-5(II) building units, forming a two-dimensional complex (3). Magnetic susceptibility measurements over a wide range of temperature exhibit the presence of both antiferromagnetic (very weak) and ferromagnetic exchanges within the tetranuclear unit structures. Density functional theory calculations (using B3LYP functional, and two different basis sets) have been performed on the complexes 1 and 2 to provide a qualitative theoretical interpretation of their overall magnetic behavior.

Building upon Supramolecular Synthons: Some Aspects of Crystal Engineering

It has been 20 years since the concept of supramolecular synthon was introduced with the purpose of rational supramolecular synthesis. While this concept has been greatly successful in employing a retrosynthetic approach in crystal engineering, the past few years have seen a continuous evolution of supramolecular synthons from being a synthetic subunit to a basic unit for understanding the dynamics of crystallization. This review attempts to give a glimpse of such developments.

An efficient design of serial and parallel memory using Quantum dot cellular automata

Quantum cellular automata (QCA) is a new technology in the nanometer scale and has been considered as one of the alternative to CMOS technology. In this paper, we describe the design and layout of a serial memory and parallel memory, showing the layout of individual memory cells. Assuming that we can fabricate cells which are separated by 10nm, memory capacities of over 1.6 Gbit/cm2 can be achieved. Simulations on the proposed memories were carried out using QCADesigner, a layout and simulation tool for QCA. During the design, we have tried to reduce the number of cells as well as to reduce the area which is found to be 86.16sq mm and 0.12 nm2 area with the QCA based memory cell. We have also achieved an increase in efficiency by 40%.These circuits are the building block of nano processors and provide us to understand the nano devices of the future.

Tissue engineering active biological machines : bio-inspired design, directed self-assembly, and characterization of muscular pumps simulating the embryonic heart

Biological machines are active devices that are comprised of cells and other biological components. These functional devices are best suited for physiological environments that support cellular function and survival. Biological machines have the potential to revolutionize the engineering of biomedical devices intended for implantation, where the human body can provide the required physiological environment. For engineering such cell-based machines, bio-inspired design can serve as a guiding platform as it provides functionally proven designs that are attainable by living cells. In the present work, a systematic approach was used to tissue engineer one such machine by exclusively using biological building blocks and by employing a bio-inspired design. Valveless impedance pumps were constructed based on the working principles of the embryonic vertebrate heart and by using cells and tissue derived from rats. The function of these tissue-engineered muscular pumps was characterized by exploring their spatiotemporal and flow behavior in order to better understand the capabilities and limitations of cells when used as the engines of biological machines.

Robust near-threshold QDI circuit analysis and design

The two most important digital-system design goals today are to reduce power consumption and to increase reliability. Reductions in power consumption improve battery life in the mobile space and reductions in energy lower operating costs in the datacenter. Increased robustness and reliability shorten down time, improve yield, and are invaluable in the context of safety-critical systems. While optimizing towards these two goals is important at all design levels, optimizations at the circuit level have the furthest reaching effects; they apply to all digital systems. This dissertation presents a study of robust minimum-energy digital circuit design and analysis. It introduces new device models, metrics, and methods of calculation—all necessary first steps towards building better systems—and demonstrates how to apply these techniques. It analyzes a fabricated chip (a full-custom QDI microcontroller designed at Caltech and taped-out in 40-nm silicon) by calculating the minimum energy operating point and quantifying the chip’s robustness in the face of both timing and functional failures.

Design and analysis of nucleic acid reaction pathways

Nucleic acids are a useful substrate for engineering at the molecular level. Designing the detailed energetics and kinetics of interactions between nucleic acid strands remains a challenge. Building on previous algorithms to characterize the ensemble of dilute solutions of nucleic acids, we present a design algorithm that allows optimization of structural features and binding energetics of a test tube of interacting nucleic acid strands. We extend this formulation to handle multiple thermodynamic states and combinatorial constraints to allow optimization of pathways of interacting nucleic acids. In both design strategies, low-cost estimates to thermodynamic properties are calculated using hierarchical ensemble decomposition and test tube ensemble focusing. These algorithms are tested on randomized test sets and on example pathways drawn from the molecular programming literature. To analyze the kinetic properties of designed sequences, we describe algorithms to identify dominant species and kinetic rates using coarse-graining at the scale of a small box containing several strands or a large box containing a dilute solution of strands.

Design for Survival: Sustainability for Planet and Structure

Buildings in Port Aransas encounter drastic environmental challenges: the potential catastrophic storm surge and high winds from a hurricane, and daily conditions hostile to buildings, vehicles, and even most vegetation. Its location a few hundred feet from the Gulf of Mexico and near-tropical latitude expose buildings to continuous high humidity, winds laden with scouring sand and corrosive salt, and extremes of temperature and ultraviolet light. Building construction methods are able to address each of these, but doing so in a sustainable way creates significant challenges. The new research building at the Marine Science Institute has been designed and is being constructed to meet the demand for both survivability and sustainability. It is tracking towards formal certification as a LEED Gold structure while being robust and resistant to the harsh coastal environment. The effects of a hurricane are mitigated by elevating buildings and providing a windproof envelope. Ground-level enclosures are designed to be sacrificial and non-structural so they can wash or blow away without imposing damage on the upper portions of the building, and only non-critical functions and equipment will be supported within them. Design features that integrate survivability with sustainability include: orientation of building axis; integral shading from direct summer sunlight; light wells; photovoltaic arrays; collection of rainwater and air conditioning condensate for use in landscape irrigation; reduced impervious cover; xeriscaping and indigenous plants; recycling of waste heat from air conditioning systems; roofing system that reflects light and heat; long life, low maintenance stainless steel, high-tensile vinyl, hard-anodized aluminum and hot-dipped galvanized mountings throughout; chloride-resistant concrete; reduced visual impact; recycling of construction materials.

Distributed Optimal Control of Cyber-Physical Systems: Controller Synthesis, Architecture Design and System Identification

The centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and spatially distributed. Both the scale and the distributed nature of these systems has motivated the decentralization of control schemes into local sub-controllers that measure, exchange and act on locally available subsets of the globally available system information. This decentralization of control logic leads to different decision makers acting on asymmetric information sets, introduces the need for coordination between them, and perhaps not surprisingly makes the resulting optimal control problem much harder to solve. In fact, shortly after such questions were posed, it was realized that seemingly simple decentralized optimal control problems are computationally intractable to solve, with the Wistenhausen counterexample being a famous instance of this phenomenon. Spurred on by this perhaps discouraging result, a concerted 40 year effort to identify tractable classes of distributed optimal control problems culminated in the notion of quadratic invariance, which loosely states that if sub-controllers can exchange information with each other at least as quickly as the effect of their control actions propagates through the plant, then the resulting distributed optimal control problem admits a convex formulation.

The identification of quadratic invariance as an appropriate means of "convexifying" distributed optimal control problems led to a renewed enthusiasm in the controller synthesis community, resulting in a rich set of results over the past decade. The contributions of this thesis can be seen as being a part of this broader family of results, with a particular focus on closing the gap between theory and practice by relaxing or removing assumptions made in the traditional distributed optimal control framework. Our contributions are to the foundational theory of distributed optimal control, and fall under three broad categories, namely controller synthesis, architecture design and system identification.

We begin by providing two novel controller synthesis algorithms. The first is a solution to the distributed H-infinity optimal control problem subject to delay constraints, and provides the only known exact characterization of delay-constrained distributed controllers satisfying an H-infinity norm bound. The second is an explicit dynamic programming solution to a two player LQR state-feedback problem with varying delays. Accommodating varying delays represents an important first step in combining distributed optimal control theory with the area of Networked Control Systems that considers lossy channels in the feedback loop. Our next set of results are concerned with controller architecture design. When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given -- indeed the task of designing this architecture is now as important as the design of the control laws themselves. To address this task, we formulate the Regularization for Design (RFD) framework, which is a unifying computationally tractable approach, based on the model matching framework and atomic norm regularization, for the simultaneous co-design of a structured optimal controller and the architecture needed to implement it. Our final result is a contribution to distributed system identification. Traditional system identification techniques such as subspace identification are not computationally scalable, and destroy rather than leverage any a priori information about the system's interconnection structure. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to estimate local dynamics within a large interconnected system. To that end we propose a promising heuristic for identifying the dynamics of a subsystem that is still connected to a large system. We exploit the fact that the transfer function of the local dynamics is low-order, but full-rank, while the transfer function of the global dynamics is high-order, but low-rank, to formulate this separation task as a nuclear norm minimization problem. Finally, we conclude with a brief discussion of future research directions, with a particular emphasis on how to incorporate the results of this thesis, and those of optimal control theory in general, into a broader theory of dynamics, control and optimization in layered architectures.