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.

Probabilistic robust control : theory and applications

In this work, the development of a probabilistic approach to robust control is motivated by structural control applications in civil engineering. Often in civil structural applications, a system's performance is specified in terms of its reliability. In addition, the model and input uncertainty for the system may be described most appropriately using probabilistic or "soft" bounds on the model and input sets. The probabilistic robust control methodology contrasts with existing H∞/μ robust control methodologies that do not use probability information for the model and input uncertainty sets, yielding only the guaranteed (i.e., "worst-case") system performance, and no information about the system's probable performance which would be of interest to civil engineers.

The design objective for the probabilistic robust controller is to maximize the reliability of the uncertain structure/controller system for a probabilistically-described uncertain excitation. The robust performance is computed for a set of possible models by weighting the conditional performance probability for a particular model by the probability of that model, then integrating over the set of possible models. This integration is accomplished efficiently using an asymptotic approximation. The probable performance can be optimized numerically over the class of allowable controllers to find the optimal controller. Also, if structural response data becomes available from a controlled structure, its probable performance can easily be updated using Bayes's Theorem to update the probability distribution over the set of possible models. An updated optimal controller can then be produced, if desired, by following the original procedure. Thus, the probabilistic framework integrates system identification and robust control in a natural manner.

The probabilistic robust control methodology is applied to two systems in this thesis. The first is a high-fidelity computer model of a benchmark structural control laboratory experiment. For this application, uncertainty in the input model only is considered. The probabilistic control design minimizes the failure probability of the benchmark system while remaining robust with respect to the input model uncertainty. The performance of an optimal low-order controller compares favorably with higher-order controllers for the same benchmark system which are based on other approaches. The second application is to the Caltech Flexible Structure, which is a light-weight aluminum truss structure actuated by three voice coil actuators. A controller is designed to minimize the failure probability for a nominal model of this system. Furthermore, the method for updating the model-based performance calculation given new response data from the system is illustrated.

Wastewater Electrolysis Cell for Environmental Pollutants Degradation and Molecular Hydrogen Generation

This study proposes a wastewater electrolysis cell (WEC) for on-site treatment of human waste coupled with decentralized molecular H₂ production. The core of the WEC includes mixed metal oxides anodes functionalized with bismuth doped TiO₂ (BiO_x/TiO₂). The BiO_x/TiO₂ anode shows reliable electro-catalytic activity to oxidize Cl- to reactive chlorine species (RCS), which degrades environmental pollutants including chemical oxygen demand (COD), protein, NH4⁺, urea, and total coliforms. The WEC experiments for treatment of various kinds of synthetic and real wastewater demonstrate sufficient water quality of effluent for reuse for toilet flushing and environmental purposes. Cathodic reduction of water and proton on stainless steel cathodes produced molecular H2 with moderate levels of current and energy efficiency. This thesis presents a comprehensive environmental analysis together with kinetic models to provide an in-depth understanding of reaction pathways mediated by the RCS and the effects of key operating parameters. The latter part of this thesis is dedicated to bilayer hetero-junction anodes which show enhanced generation efficiency of RCS and long-term stability.

Chapter 2 describes the reaction pathway and kinetics of urea degradation mediated by electrochemically generated RCS. The urea oxidation involves chloramines and chlorinated urea as reaction intermediates, for which the mass/charge balance analysis reveals that N₂ and CO₂ are the primary products. Chapter 3 investigates direct-current and photovoltaic powered WEC for domestic wastewater treatment, while Chapter 4 demonstrates the feasibility of the WEC to treat model septic tank effluents. The results in Chapter 2 and 3 corroborate the active roles of chlorine radicals (Cl•/Cl₂^-•) based on iR-compensated anodic potential (thermodynamic basis) and enhanced pseudo-first-order rate constants (kinetic basis). The effects of operating parameters (anodic potential and [Cl^-] in Chapter 3; influent dilution and anaerobic pretreatment in Chapter 4) on the rate and current/energy efficiency of pollutants degradation and H₂ production are thoroughly discussed based on robust kinetic models. Chapter 5 reports the generation of RCS on Ir_0.7Ta_0.3O_y/Bi_xTi_1-xO_z hetero-junction anodes with enhanced rate, current efficiency, and long-term stability compared to the Ir_0.7Ta_0.3O_y anode. The effects of surficial Bi concentration are interrogated, focusing on relative distributions between surface-bound hydroxyl radical and higher oxide.

Investigations of DNA-mediated protein oxidation

DNA charge transport (CT) involves the efficient transfer of electrons or electron holes through the DNA π-stack over long molecular distances of at least 100 base-pairs. Despite this shallow distance dependence, DNA CT is sensitive to mismatches or lesions that disrupt π-stacking and is critically dependent on proper electronic coupling of the donor and acceptor moieties into the base stack. Favorable DNA CT is very rapid, occurring on the picosecond timescale. Because of this speed, electron holes equilibrate along the DNA π-stack, forming a characteristic pattern of DNA damage at low oxidation potential guanine multiplets. Furthermore, DNA CT may be used in a biological context. DNA processing enzymes with 4Fe4S clusters can perform DNA-mediated electron transfer (ET) self-exchange reactions with other 4Fe4S cluster proteins, even if the proteins are quite dissimilar, as long as the DNA-bound [4Fe4S]^3+/2+ redox potentials are conserved. This mechanism would allow low copy number DNA repair proteins to find their lesions efficiently within the cell. DNA CT may also be used biologically for the long-range, selective activation of redox-active transcription factors. Within this work, we pursue other proteins that may utilize DNA CT within the cell and further elucidate aspects of the DNA-mediated ET self-exchange reaction of 4Fe4S cluster proteins.

Dps proteins, bacterial mini-ferritins that protect DNA from oxidative stress, are implicated in the survival and virulence of pathogenic bacteria. One aspect of their protection involves ferroxidase activity, whereby ferrous iron is bound and oxidized selectively by hydrogen peroxide, thereby preventing formation of damaging hydroxyl radicals via Fenton chemistry. Understanding the specific mechanism by which Dps proteins protect the bacterial genome could inform the development of new antibiotics. We investigate whether DNA-binding E. coli Dps can utilize DNA CT to protect the genome from a distance. An intercalating ruthenium photooxidant was employed to generate oxidative DNA damage via the flash-quench technique, which localizes to a low potential guanine triplet. We find that Dps loaded with ferrous iron, in contrast to Apo-Dps and ferric iron-loaded Dps which lack available reducing equivalents, significantly attenuates the yield of oxidative DNA damage at the guanine triplet. These data demonstrate that ferrous iron-loaded Dps is selectively oxidized to fill guanine radical holes, thereby restoring the integrity of the DNA. Luminescence studies indicate no direct interaction between the ruthenium photooxidant and Dps, supporting the DNA-mediated oxidation of ferrous iron-loaded Dps. Thus DNA CT may be a mechanism by which Dps efficiently protects the genome of pathogenic bacteria from a distance.

Further work focused on spectroscopic characterization of the DNA-mediated oxidation of ferrous iron-loaded Dps. X-band EPR was used to monitor the oxidation of DNA-bound Dps after DNA photooxidation via the flash-quench technique. Upon irradiation with poly(dGdC)₂, a signal arises with g = 4.3, consistent with the formation of mononuclear high-spin Fe(III) sites of low symmetry, the expected oxidation product of Dps with one iron bound at each ferroxidase site. When poly(dGdC)₂ is substituted with poly(dAdT)₂, the yield of Dps oxidation is decreased significantly, indicating that guanine radicals facilitate Dps oxidation. The more favorable oxidation of Dps by guanine radicals supports the feasibility of a long-distance protection mechanism via DNA CT where Dps is oxidized to fill guanine radical holes in the bacterial genome produced by reactive oxygen species.

We have also explored possible electron transfer intermediates in the DNA-mediated oxidation of ferrous iron-loaded Dps. Dps proteins contain a conserved tryptophan residue in close proximity to the ferroxidase site (W52 in E. coli Dps). In comparison to WT Dps, in EPR studies of the oxidation of ferrous iron-loaded Dps following DNA photooxidation, W52Y and W52A mutants were deficient in forming the characteristic EPR signal at g = 4.3, with a larger deficiency for W52A compared to W52Y. In addition to EPR, we also probed the role of W52 Dps in cells using a hydrogen peroxide survival assay. Bacteria containing W52Y Dps survived the hydrogen peroxide challenge more similarly to those containing WT Dps, whereas cells with W52A Dps died off as quickly as cells without Dps. Overall, these results suggest the possibility of W52 as a CT hopping intermediate.

DNA-modified electrodes have become an essential tool for the study of the redox chemistry of DNA processing enzymes with 4Fe4S clusters. In many cases, it is necessary to investigate different complex samples and substrates in parallel in order to elucidate this chemistry. Therefore, we optimized and characterized a multiplexed electrochemical platform with the 4Fe4S cluster base excision repair glycosylase Endonuclease III (EndoIII). Closely packed DNA films, where the protein has limited surface accessibility, produce EndoIII electrochemical signals sensitive to an intervening mismatch, indicating a DNA-mediated process. Multiplexed analysis allowed more robust characterization of the CT-deficient Y82A EndoIII mutant, as well as comparison of a new family of mutations altering the electrostatics surrounding the 4Fe4S cluster in an effort to shift the reduction potential of the cluster. While little change in the DNA-bound midpoint potential was found for this family of mutants, likely indicating the dominant effect of DNA-binding on establishing the protein redox potential, significant variations in the efficiency of DNA-mediated electron transfer were apparent. On the basis of the stability of these proteins, examined by circular dichroism, we proposed that the electron transfer pathway in EndoIII can be perturbed not only by the removal of aromatic residues but also through changes in solvation near the cluster.

While the 4Fe4S cluster of EndoIII is relatively insensitive to oxidation and reduction in solution, we have found that upon DNA binding, the reduction potential of the [4Fe4S]^3+/2+ couple shifts negatively by approximately 200 mV, bringing this couple into a physiologically relevant range. Demonstrated using electrochemistry experiments in the presence and absence of DNA, these studies do not provide direct molecular evidence for the species being observed. Sulfur K-edge X-ray absorbance spectroscopy (XAS) can be used to probe directly the covalency of iron-sulfur clusters, which is correlated to their reduction potential. We have shown that the Fe-S covalency of the 4Fe4S cluster of EndoIII increases upon DNA binding, stabilizing the oxidized [4Fe4S]³⁺ cluster, consistent with a negative shift in reduction potential. The 7% increase in Fe-S covalency corresponds to an approximately 150 mV shift, remarkably similar to DNA electrochemistry results. Therefore we have obtained direct molecular evidence for the shift in 4Fe4S reduction potential of EndoIII upon DNA binding, supporting the feasibility of our model whereby these proteins can utilize DNA CT to cooperate in order to efficiently find DNA lesions inside cells.

In conclusion, in this work we have explored the biological applications of DNA CT. We discovered that the DNA-binding bacterial ferritin Dps can protect the bacterial genome from a distance via DNA CT, perhaps contributing to pathogen survival and virulence. Furthermore, we optimized a multiplexed electrochemical platform for the study of the redox chemistry of DNA-bound 4Fe4S cluster proteins. Finally, we have used sulfur K-edge XAS to obtain direct molecular evidence for the negative shift in 4Fe4S cluster reduction potential of EndoIII upon DNA binding. These studies contribute to the understanding of DNA-mediated protein oxidation within cells.

Robust Control of Evolutionary Dynamics

The application of principles from evolutionary biology has long been used to gain new insights into the progression and clinical control of both infectious diseases and neoplasms. This iterative evolutionary process consists of expansion, diversification and selection within an adaptive landscape - species are subject to random genetic or epigenetic alterations that result in variations; genetic information is inherited through asexual reproduction and strong selective pressures such as therapeutic intervention can lead to the adaptation and expansion of resistant variants. These principles lie at the center of modern evolutionary synthesis and constitute the primary reasons for the development of resistance and therapeutic failure, but also provide a framework that allows for more effective control.

A model system for studying the evolution of resistance and control of therapeutic failure is the treatment of chronic HIV-1 infection by broadly neutralizing antibody (bNAb) therapy. A relatively recent discovery is that a minority of HIV-infected individuals can produce broadly neutralizing antibodies, that is, antibodies that inhibit infection by many strains of HIV. Passive transfer of human antibodies for the prevention and treatment of HIV-1 infection is increasingly being considered as an alternative to a conventional vaccine. However, recent evolution studies have uncovered that antibody treatment can exert selective pressure on virus that results in the rapid evolution of resistance. In certain cases, complete resistance to an antibody is conferred with a single amino acid substitution on the viral envelope of HIV.

The challenges in uncovering resistance mechanisms and designing effective combination strategies to control evolutionary processes and prevent therapeutic failure apply more broadly. We are motivated by two questions: Can we predict the evolution to resistance by characterizing genetic alterations that contribute to modified phenotypic fitness? Given an evolutionary landscape and a set of candidate therapies, can we computationally synthesize treatment strategies that control evolution to resistance?

To address the first question, we propose a mathematical framework to reason about evolutionary dynamics of HIV from computationally derived Gibbs energy fitness landscapes -- expanding the theoretical concept of an evolutionary landscape originally conceived by Sewall Wright to a computable, quantifiable, multidimensional, structurally defined fitness surface upon which to study complex HIV evolutionary outcomes.

To design combination treatment strategies that control evolution to resistance, we propose a methodology that solves for optimal combinations and concentrations of candidate therapies, and allows for the ability to quantifiably explore tradeoffs in treatment design, such as limiting the number of candidate therapies in the combination, dosage constraints and robustness to error. Our algorithm is based on the application of recent results in optimal control to an HIV evolutionary dynamics model and is constructed from experimentally derived antibody resistant phenotypes and their single antibody pharmacodynamics. This method represents a first step towards integrating principled engineering techniques with an experimentally based mathematical model in the rational design of combination treatment strategies and offers predictive understanding of the effects of combination therapies of evolutionary dynamics and resistance of HIV. Preliminary in vitro studies suggest that the combination antibody therapies predicted by our algorithm can neutralize heterogeneous viral populations despite containing resistant mutations.