Physical Design Methodologies for Low Power and Reliable 3D ICs

As the semiconductor industry struggles to maintain its momentum down the path following the Moore's Law, three dimensional integrated circuit (3D IC) technology has emerged as a promising solution to achieve higher integration density, better performance, and lower power consumption. However, despite its significant improvement in electrical performance, 3D IC presents several serious physical design challenges. In this dissertation, we investigate physical design methodologies for 3D ICs with primary focus on two areas: low power 3D clock tree design, and reliability degradation modeling and management. Clock trees are essential parts for digital system which dissipate a large amount of power due to high capacitive loads. The majority of existing 3D clock tree designs focus on minimizing the total wire length, which produces sub-optimal results for power optimization. In this dissertation, we formulate a 3D clock tree design flow which directly optimizes for clock power. Besides, we also investigate the design methodology for clock gating a 3D clock tree, which uses shutdown gates to selectively turn off unnecessary clock activities. Different from the common assumption in 2D ICs that shutdown gates are cheap thus can be applied at every clock node, shutdown gates in 3D ICs introduce additional control TSVs, which compete with clock TSVs for placement resources. We explore the design methodologies to produce the optimal allocation and placement for clock and control TSVs so that the clock power is minimized. We show that the proposed synthesis flow saves significant clock power while accounting for available TSV placement area. Vertical integration also brings new reliability challenges including TSV's electromigration (EM) and several other reliability loss mechanisms caused by TSV-induced stress. These reliability loss models involve complex inter-dependencies between electrical and thermal conditions, which have not been investigated in the past. In this dissertation we set up an electrical/thermal/reliability co-simulation framework to capture the transient of reliability loss in 3D ICs. We further derive and validate an analytical reliability objective function that can be integrated into the 3D placement design flow. The reliability aware placement scheme enables co-design and co-optimization of both the electrical and reliability property, thus improves both the circuit's performance and its lifetime. Our electrical/reliability co-design scheme avoids unnecessary design cycles or application of ad-hoc fixes that lead to sub-optimal performance. Vertical integration also enables stacking DRAM on top of CPU, providing high bandwidth and short latency. However, non-uniform voltage fluctuation and local thermal hotspot in CPU layers are coupled into DRAM layers, causing a non-uniform bit-cell leakage (thereby bit flip) distribution. We propose a performance-power-resilience simulation framework to capture DRAM soft error in 3D multi-core CPU systems. In addition, a dynamic resilience management (DRM) scheme is investigated, which adaptively tunes CPU's operating points to adjust DRAM's voltage noise and thermal condition during runtime. The DRM uses dynamic frequency scaling to achieve a resilience borrow-in strategy, which effectively enhances DRAM's resilience without sacrificing performance. The proposed physical design methodologies should act as important building blocks for 3D ICs and push 3D ICs toward mainstream acceptance in the near future.

A Bayesian optimization algorithm for the nurse scheduling problem

A Bayesian optimization algorithm for the nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurse’s assignment. Unlike our previous work that used GAs to implement implicit learning, the learning in the proposed algorithm is explicit, i.e. eventually, we will be able to identify and mix building blocks directly. The Bayesian optimization algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated by using the corresponding conditional probabilities, until all variables have been generated, i.e. in our case, a new rule string has been obtained. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again using the current set of promising rule strings. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed approach might be suitable for other scheduling problems.

Raman Spectroscopy and DFT calculations for the Electronic Structure Characterization of Conjugated Polymers

In the last three decades, there has been a broad academic and industrial interest in conjugated polymers as semiconducting materials for organic electronics. Their applications in polymer light-emitting diodes (PLEDs), polymer solar cells (PSCs), and organic field-effect transistors (OFETs) offer opportunities for the resolution of energy issues as well as the development of display and information technologies1. Conjugated polymers provide several advantages including low cost, light weight, good flexibility, as well as solubility which make them readily processed and easily printed, removing the conventional photolithography for patterning2. A large library of polymer semiconductors have been synthesized and investigated with different building blocks, such as acenes or thiophene and derivatives, which have been employed to design new materials according to individual demands for specific applications. To design ideal conjugated polymers for specific applications, some general principles should be taken into account, including (i) side chains (ii) molecular weights, (iii) band gap and HOMO and LUMO energy levels, and (iv) suited morphology.3-6 The aim of this study is to elucidate the impact that substitution exerts on the molecular and electronic structure of π-conjugated polymers with outstanding performances in organic electronic devices. Different configurations of the π-conjugated backbones are analyzed: (i) donor-acceptor configuration, (ii) 1D lineal or 2D branched conjugated backbones, and (iii) encapsulated polymers (see Figure 1). Our combined vibrational spectroscopy and DFT study shows that small changes in the substitution pattern and in the molecular configuration have a strong impact on the electronic characteristics of these polymers. We hope this study can advance useful structure-property relationships of conjugated polymers and guide the design of new materials for organic electronic applications.

Synthetic Circuits for Feedback and Detection in Bacteria

Synthetic biology, by co-opting molecular machinery from existing organisms, can be used as a tool for building new genetic systems from scratch, for understanding natural networks through perturbation, or for hybrid circuits that piggy-back on existing cellular infrastructure. Although the toolbox for genetic circuits has greatly expanded in recent years, it is still difficult to separate the circuit function from its specific molecular implementation. In this thesis, we discuss the function-driven design of two synthetic circuit modules, and use mathematical models to understand the fundamental limits of circuit topology versus operating regimes as determined by the specific molecular implementation. First, we describe a protein concentration tracker circuit that sets the concentration of an output protein relative to the concentration of a reference protein. The functionality of this circuit relies on a single negative feedback loop that is implemented via small programmable protein scaffold domains. We build a mass-action model to understand the relevant timescales of the tracking behavior and how the input/output ratios and circuit gain might be tuned with circuit components. Second, we design an event detector circuit with permanent genetic memory that can record order and timing between two chemical events. This circuit was implemented using bacteriophage integrases that recombine specific segments of DNA in response to chemical inputs. We simulate expected population-level outcomes using a stochastic Markov-chain model, and investigate how inferences on past events can be made from differences between single-cell and population-level responses. Additionally, we present some preliminary investigations on spatial patterning using the event detector circuit as well as the design of stationary phase promoters for growth-phase dependent activation. These results advance our understanding of synthetic gene circuits, and contribute towards the use of circuit modules as building blocks for larger and more complex synthetic networks.

Sintonia automática de controladores PID: uma abordagem neuro - genética

Dissertação de dout. em Electrónica e Computação, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2004

Trajetória profissional de professoras do ensino médio : sentidos e usos de tecnologias digitais na sala de aula

Tese (doutorado)—Universidade de Brasília, Instituto de Psicologia, Programa de Pós-Graduação em Processos de Desenvolvimento Humano e Saúde, 2016.

Feasibility study and flow scheduling optimization of a multi-product pipeline system

The first goal of this study is to analyse a real-world multiproduct onshore pipeline system in order to verify its hydraulic configuration and operational feasibility by constructing a simulation model step by step from its elementary building blocks that permits to copy the operation of the real system as precisely as possible. The second goal is to develop this simulation model into a user-friendly tool that one could use to find an “optimal” or “best” product batch schedule for a one year time period. Such a batch schedule could change dynamically as perturbations occur during operation that influence the behaviour of the entire system. The result of the simulation, the ‘best’ batch schedule is the one that minimizes the operational costs in the system. The costs involved in the simulation are inventory costs, interface costs, pumping costs, and penalty costs assigned to any unforeseen situations. The key factor to determine the performance of the simulation model is the way time is represented. In our model an event based discrete time representation is selected as most appropriate for our purposes. This means that the time horizon is divided into intervals of unequal lengths based on events that change the state of the system. These events are the arrival/departure of the tanker ships, the openings and closures of loading/unloading valves of storage tanks at both terminals, and the arrivals/departures of trains/trucks at the Delivery Terminal. In the feasibility study we analyse the system’s operational performance with different Head Terminal storage capacity configurations. For these alternative configurations we evaluated the effect of different tanker ship delay magnitudes on the number of critical events and product interfaces generated, on the duration of pipeline stoppages, the satisfaction of the product demand and on the operative costs. Based on the results and the bottlenecks identified, we propose modifications in the original setup.

The actinin family of actin crosslinking proteins: natural functions and potential applications in synthetic biology

Actinin and spectrin proteins are members of the Spectrin Family of Actin Crosslinking Proteins. The importance of these proteins in the cytoskeleton is demonstrated by the fact that they are common targets for disease causing mutations. In their most prominent roles, actinin and spectrin are responsible for stabilising and maintaining the muscle architecture during contraction, and providing shape and elasticity to the red blood cell in circulation, respectively. To carry out such roles, actinin and spectrin must possess important mechanical and physical properties. These attributes are desirable when choosing a building block for protein-based nanoconstruction. In this study, I assess the contribution of several disease-associated mutations in the actinin-1 actin binding domain that have recently been linked to a rare platelet disorder, congenital macrothrombocytopenia. I investigate the suitability of both actinin and spectrin proteins as potential building blocks for nanoscale structures, and I evaluate a fusion-based assembly strategy to bring about self-assembly of protein nanostructures. I report that the actinin-1 mutant proteins display increased actin binding compared to WT actinin-1 proteins. I find that both actinin and spectrin proteins exhibit enormous potential as nano-building blocks in terms of their stability and ability to self-assemble, and I successfully design and create homodimeric and heterodimeric bivalent building blocks using the fusion-based assembly strategy. Overall, this study has gathered helpful information that will contribute to furthering the advancement of actinin and spectrin knowledge in terms of their natural functions, and potential unnatural functions in protein nanotechnology.

Cognitive Assessment System (CAS): Psychometric studies with Portuguese children from 7 to 15 years.

The Cognitive Assessment System (CAS) is a new measure of cognitive abilities based on the Planning, Attention, Simultaneous and Successive (PASS) Theory. This theory is derived from research in neuropsychological and cognitive Psychology with particular emphasis on the work of Luria (1973). According to Naglieri (1999) and Naglieri and Das (1997), the PASS cognitive processes are the basic building blocks of human intellectual functioning. Planning processes provide cognitive control, utilization of processes and knowledge, intentionality, and self-regulation to achieve a desired goal; Attention processes provide focused, selective cognitive activity and resistance to distraction; and, Simultaneous and Successive processes are the two forms of operating on information. The PASS theory has had a strong empirical base prior to the publication of the CAS (see Das, Naglieri & Kirby, 1994), and its research foundation remains strong (see Naglieri, 1999; Naglieri & Das, 1997). The four basic psychological processes can be used to (1) gain an understanding of how well a child thinks; (2) discover the child’s strengths and needs, which can then be used for effective differential diagnosis; (3) conduct fair assessment; and (4) select or design appropriate interventions. Compared to the traditional intelligence tests, including IQ tests, the Cognitive Assessment System (CAS) has the great advantage of relying on a modern theory of cognitive functioning, linking theory with practice.

Unlocking the Potential of Women in the Rural Development Process of Republic of Srpska: The Role of Extension Service

In Bosnia Herzegovina the development of clear policy objectives and endorsement of a long-term, coherent and mutual agricultural and rural development policy have also been affected by structural problems: a lack of reliable information on population and other relevant issues, the absence of an adequate land registry system and cadastre. Moreover in BiH the agricultural and rural sectors are characterized by many factors that have typically affected transition countries such as land fragmentation, lack of agricultural mechanization and outdated production technologies, and rural aging, high unemployment and out-migration. In such a framework the condition and role of women in rural areas suffered for the lack of gender disaggregated data and a consequent poor information that lead to the exclusion of gender related questions in the agenda of public institutions and to the absence of targeted policy interventions. The aim of the research is to investigate the role and condition of women in the rural development process of Republic of Srpska and to analyze the capacity of extension services to stimulate their empowerment. Specific research questions include the status of women in the rural areas of Republic of Srpska, the role of government in fostering the empowerment of rural women, and the role of the extension service in supporting rural women. The methodology - inspired by the case study method developed by R. Yin - is designed along the three specific research questions that are used as building blocks. Each of the three research questions is investigated with a combination of methodological tools - including surveys, experts interviews and focus groups - aimed to overcome the lack of data and knowledge that characterize the research objectives.

Peptide-based low molecular weight gelators for the preparation of self-assembled materials

Low molecular weight gelators (LMWGs) based on pseudo-peptides are here studied for the preparation of supramolecular materials. These compounds can self-assemble through non-covalent interactions such as hydrogen bonds and π-π stacking, forming fibres and gels. A wide variety of materials can be prepared starting from these building blocks, which can be tuned and functionalised depending on the application. In this work, derivatives of the three aromatic amino acids L-Phenylalanine, L-Tyrosine and L-DOPA (3,4-dihydroxiphenylalanine) were synthesised and tested as gelators for water or organic solvents. First, the optimal gelating conditions were studied for each compound, varying concentration, solvent and trigger. Then the materials were characterised in terms of mechanical properties and morphology. Water remediation from dye pollution was the first focus of this work. Organogels were studied as absorbent of dyes from contaminated water. Hydrogels functionalised with TiO2 nanoparticles and graphene platelets were proposed as efficient materials for the photo-degradation of dyes. An efficient method for the incorporation of graphene inside hydrogels using the gelator itself as dispersant was proposed. In these materials a high storage modulus coexists with good self-healing and biocompatibility. The incorporation of a mineral phase inside the gel matrix was then investigated, leading to the preparation of composite organic/inorganic materials. In a first study, the growth of calcium carbonate crystals was achieved inside the hydrogel, which preserved its structure after crystal formation. Then the self-assembled fibres made of LMWGs were used for the first time instead of the polymeric ones as reinforcement inside calcium phosphate cements (CPCs) for bone regeneration. Gel-to-crystal transitions occurring with time in a metastable gel were also examined. The formation of organic crystals in gels can be achieved in multicomponent systems, in which a second gelator constitutes the independent gel network. Finally, some compounds unable to gelate were tested as underwater adhesives.

Preparation and characterization of multifunctional bio-based polymers exhibiting enhanced properties

Driven by environmental reasons and the expected depletion of crude oil, bio-based polymers are currently undergoing a renaissance in the attempt to replace fossil-based ones. The present work aims at contributing in the development of the steps that start from biomass and move to new polymeric multifunctional materials. The study focuses on two bio-based building blocks (itaconic and vanillic acids) characterized by exploitable functionalities, i.e. a lateral double bond and a substituted aromatic ring respectively, able to confer interesting properties to the final polymers. The lateral double bond of dimethyl itaconate was functionalized via thia-Michael addition reaction obtaining a thermo-stable building block that can undergo polycondensation under classical conditions of reaction. The addition of a long lateral chain allows the polymer to express antimicrobial activity against Staphylococcus aureus making it attractive for packaging and targeting antimicrobial applications. Moreover, the architecture of the homopolymer was modified by means of copolymerization with dimethyl 2,5-furandicarboxylate thus improving the rigidity and obtaining a thermo-processable material. Potential applications as thermoset or thermoplastic material have been discussed. As concerns vanillic acid, the presence of aromatic rings on the polymer backbone imparts high thermal stability, but brittle behaviour in the homopolymer. Therefore, the architecture of the polyester was successfully tuned by means of copolymerization with a flexible bio-based comonomer, i.e. ω-pentadecalactone, providing processable random copolymers. An in depth investigation of water transport mechanism has been undertaken on the synthesized polyesters. Since the copolymers present a succession of aromatic and aliphatic units, as a consequence of the chemical structure water vapor permeability interposes between polyethylene and poly(ethylene terephthalate) proving that the copolyesters are suitable for packaging applications. Moving towards a sustainable model of development, novel sustainable synthetic pathways for the eco-design of new bio-based polymeric structures with high value functionalities and different potential applications have been successfully developed.

Synthesis of new non-fullerene acceptors based on indacenodithiophene core for organic solar cells

Due to the low cost, lightness and flexibility, Polymer Solar Cell (PSC) technology is considered one of the most promising energy technologies. In the past decades, PSCs using fullerenes or fullerene derivatives as the electron acceptors have made great progress with best power conversion efficiency (PCE) reaching 11%. However, fullerene type electron acceptors have several drawbacks such as complicated synthesis, a low light absorption coefficient and poor tuning in energy levels, which prevent the further development of fullerene-based PSCs. Hence the need to have a new class of electron acceptors as an alternative to conventional fullerene compounds. Non-fullerene acceptors (NFAs) have developed rapidly in the last years and the maximum PCEs have exceeded 14% for single-junction cells and 17% for double-junction tandem cells. By combining an electron-donating backbone, generally with several fused rings with electron-withdrawing units, we can simply construct NFA of the acceptor–donor–acceptor type (A–D–A). Versatile molecular structures have been developed using methods such as acceptor motif engineering and donor motif engineering. However, there are only a few electron-donating backbones that have been proved to be successful. Therefore, it is still necessary to develop promising building blocks to further enrich the structural diversity. An indacenodithiophene (IDT) unit with just five fused rings has a sufficiently rigid coplanar structure, which has been regarded as one of the promising electron-rich units to design high-performance A–D–A NFAs. In this work, performed at the King Abdullah University of Science and Technology in Saudi Arabia, a new nine-cyclic building block (TBIDT) with a two benzothiophene unit was synthesized and used for designing new non-fullerene electron acceptors.

Multi-functional electrocatalysts for CO2 reduction reaction: towards the modulation of selectivity

The electrocatalytic reduction of CO2 (CO2RR) is a captivating strategy for the conversion of CO2 into fuels, to realize a carbon neutral circular economy. In the recent years, research has focused on the development of new materials and technology capable of capturing and converting CO2 into useful products. The main problem of CO2RR is given by its poor selectivity, which can lead to the formation of numerous reaction products, to the detriment of efficiencies. For this reason, the design of new electrocatalysts that selectively and efficiently reduce CO2 is a fundamental step for the future exploitation of this technology. Here we present a new class of electrocatalysts, designed with a modular approach, namely, deriving from the combination of different building blocks in a single nanostructure. With this approach it is possible to obtain materials with an innovative design and new functionalities, where the interconnections between the various components are essential to obtain a highly selective and efficient reduction of CO2, thus opening up new possibilities in the design of optimized electrocatalytic materials. By combining the unique physic-chemical properties of carbon nanostructures (CNS) with nanocrystalline metal oxides (MO), we were able to modulate the selectivity of CO2RR, with the production of formic acid and syngas at low overpotentials. The CNS have not only the task of stabilizing the MO nanoparticles, but the creation of an optimal interface between two nanostructures is able to improve the catalytic activity of the active phase of the material. While the presence of oxygen atoms in the MO creates defects that accelerate the reaction kinetics and stabilize certain reaction intermediates, selecting the reaction pathway. Finally, a part was dedicated to the study of the experimental parameters influencing the CO2RR, with the aim of improving the experimental setup in order to obtain commercial catalytic performances.

Radio frequency communication and fault detection for railway signalling

The continuous and swift progression of both wireless and wired communication technologies in today's world owes its success to the foundational systems established earlier. These systems serve as the building blocks that enable the enhancement of services to cater to evolving requirements. Studying the vulnerabilities of previously designed systems and their current usage leads to the development of new communication technologies replacing the old ones such as GSM-R in the railway field. The current industrial research has a specific focus on finding an appropriate telecommunication solution for railway communications that will replace the GSM-R standard which will be switched off in the next years. Various standardization organizations are currently exploring and designing a radiofrequency technology based standard solution to serve railway communications in the form of FRMCS (Future Railway Mobile Communication System) to substitute the current GSM-R. Bearing on this topic, the primary strategic objective of the research is to assess the feasibility to leverage on the current public network technologies such as LTE to cater to mission and safety critical communication for low density lines. The research aims to identify the constraints, define a service level agreement with telecom operators, and establish the necessary implementations to make the system as reliable as possible over an open and public network, while considering safety and cybersecurity aspects. The LTE infrastructure would be utilized to transmit the vital data for the communication of a railway system and to gather and transmit all the field measurements to the control room for maintenance purposes. Given the significance of maintenance activities in the railway sector, the ongoing research includes the implementation of a machine learning algorithm to detect railway equipment faults, reducing time and human analysis errors due to the large volume of measurements from the field.