Chemistry of Lead Halide Perovskites: Aspects of Solution-Gelation and Acid-Base Reactions with Aliphatic Amines
Contributors: Kerner, Ross, Rand, Barry P., Electrical Engineering Department
... Metal halide perovskites are an exciting and promising class of materials for optoelectronic device applications. Advancement of perovskite photovoltaic and light emitting diode lab-scale efficiencies have increased to or exceeded the performance of many established semiconductor technologies, but on a much shorter time scale. The rapid evolution of halide perovskite technology owes largely to the knowledge base gained from previous thin film technologies as well as a large amount of empirical improvements in processing and device architecture. However, there exist several barriers to commercialization of halide perovskites, mainly, long-term material stability and device operation. These challenges stem from the strong chemical reactivity of halide perovskite materials. Reactions taking place in solution while processing and in the solid-state during device fabrication/characterization lead to many complications and potentially obfuscate interpretation of results. These unique properties also make perovskites a rich platform by which to study many interesting and novel photo-electrochemical phenomena. In this thesis, we study the chemical properties of halide perovskites elucidating aspects of solution-gelation chemistry, the effect of stoichiometry on nano-scale composition, acid-base reactions with simple additives in solution, and solid-state reduction-oxidation reactions influencing electrochemical stability. Fundamental insight gained from these detailed studies facilitate significant improvements targeting specific applications such as fabricating ultrasmooth, ultrathin perovskite films with high emissivity and exploiting impurity chemistry at optimal concentrations leading to defect passivation. These results demonstrate the benefits of identifying chemical reaction mechanisms relevant to halide perovskites. Understanding and predicting how perovskites will react with other material systems and conditions is paramount for progressing the field and overcoming challenges to commercialization of this technology.
Contributors: Zhang, Jintao, Verma, Naveen, Electrical Engineering Department
... Embedded sensor signals from an increasing variety of sources are enabling a broad range of intelligent systems. For instance, the systems aim to gain information about the state of the world, including its human inhabitants. However, the extraction of such information from embedded signals is challenging, since the signals naturally arise from complex physics of real-world processes. Machine-learning algorithms are addressing this challenge by enabling the construction of models for inferences from such complex signals, by using the data themselves. A key focus thus becomes the realization of such algorithms in highly energy-constrained sensing devices, despite the increasing compute complexity of the algorithms. In energy-constrained systems, a conventional way to resolve this problem is to employ application-specific circuits. In this thesis, we have proposed using mixed-signal computation within unconventional architectures to overcome fundamental limitations that are faced in traditional digital application-specific architectures. But to maximize energy efficiency, the new architectures must avoid overheads typically incurred to correct mixed-signal circuit non-idealities. In order to maintain high overall system level performance, we also exploit the machine-learning approach of Data-Driven Hardware Resilience (DDHR), which involves statistical learning using data processed by the non-ideal circuits themselves, such that the machine-learning model optimally adapts to the non-idealities. This leads to substantial hardware-level relaxation and thus the potential for highly efficient system implementations. To demonstrate our ideas, multiple hardware designs that are tested via silicon-CMOS prototypes are demonstrated. We first present a Time-domain Analog-to-Digital Converter (ADC) with Support Vector Machine (SVM) accelerator, to show the idea of DDHR in an embedded seizure detection system when overcoming analog non-idealities. Then, a SAR-ADC based matrix multiplier, referred to as the Matrix-Multiplying ADC (MMADC), is demonstrated as an example for mixed-signal computing. Then, an SRAM-based strong classifier (ClassRAM) is demonstrated. Further, system-level trade-offs and specialized algorithms are analyzed and developed, based on the in-memory architecture extended from ClassRAM, which enhance the application-level computational scalability of the architectures.
Contributors: Gramespacher, Josef Andrew, Muir, Tom W, Molecular Biology Department
... The discovery and characterization of inteins has led to the development of powerful applications capable of modulating protein structure and function through protein splicing. However, while inteins have found great utility in-vitro with protein semi-synthesis applications, their use as tools to modify proteins in living systems has been limited by the-auto catalytic nature of the splicing reaction, which makes temporal control of their activity difficult. To address this issue, a variety of conditional protein splicing (CPS) methods have been developed to try and regulate the splicing reaction so that intein activity can be activated only upon addition of a specified trigger. However, these CPS methods have largely relied on inteins that suffer from a variety of unfavorable characteristics that constrain their broader utility, including slow splicing kinetics, poor stability, and stringent extein dependency. In contrast, the recently characterized fast splicing split inteins such as the DnaE intein Npu, are less susceptible to these limitations. Therefore, CPS methods based on naturally split fast splicing inteins should help to make in-cell intein based tools more broadly accessible. This thesis attempts to address this issue by utilizing a basic mechanistic understanding of how the split intein Npu assembles and splices to develop intein zymogens, the first CPS method that effectively controls the association and splicing of multiple fast splicing split inteins while remaining amenable to a diverse set of triggers. Utilizing our understanding of how the caged inteins function, we then developed a general method that can be easily and effectively applied to increase expression and functionality of split N-inteins and split protein-intein fusions, which are otherwise prone to aggregation. Lastly, we further engineer the intein zymogens so that close proximity of the caged intein fragments can be used to overcome splicing inhibition, paving the road for applications that have both temporal and spatial control over protein function. In combination, these methods should make it possible to develop previously impractical or intractable intein based applications and generally expand their utility in cells.
Contributors: Yang, Junnan, Mauzerall, Denise L., Public and International Affairs Department
... China’s rapid economic growth over the past few decades has been fueled by the coal-dominated energy system. The increasing consumption of coal and other fossil fuels has resulted in a dramatic increase in China’s greenhouse gas (GHG) emissions and worsening ambient air quality. The Chinese government has designed and implemented various deployment policies to support the transition toward significantly less coal and other fossil fuel consumption. My dissertation focuses on the climate, air quality, and industrial growth co-benefits of various deployment policies in China. It includes three analytical chapters. Chapter 2 analyzes the climate, air quality and human health benefits of various solar PV deployment scenarios in China in 2030. I find that deploying distributed PV in the east with inter-provincial transmission maximizes potential CO2 reductions and air quality-related health benefits. Deployment in the east with inter-provincial transmission results in the largest benefits because it maximizes displacement of the dirtiest coal-fired power plants and minimizes PV curtailment, which is more likely to occur without inter-provincial transmission. Chapter 3 analyzes the climate, air quality and human health implications of replacing small heating stoves with gas and electric heating in China. I examine the implications of using gas (conventional gas or coal-based synthetic natural gas (SNG)) and electricity (either resistance heaters or air-source heat pumps) for heating. I find deploying heat pumps as a substitute for small solid fuel stoves for heating has the greatest long-term potential of significant air quality and climate co-benefits as China further decarbonizes its power sector. Chapter 4 analyzes the role of deployment policies in promoting industrial growth in China’s wind, solar PV and Lithium-ion battery industries. I argue that deployment policies are effective to support industrial growth when the end uses of the clean energy technology are relatively few and concentrated. For battery storage technology, I find that there are multiple use cases of storage systems in the power sector, which makes direct subsidization for battery storage systems less effective in promoting the Li-ion battery industry compared to China’s wind and solar industries.
Contributors: Rogers, Hope Hayes, Johnson, Claudia L, Nord, Deborah, English Department
... Ann Radcliffe’s The Mysteries of Udolpho (1794), Jane Austen’s Emma (1815), Elizabeth Gaskell’s Cranford (1853), Margaret Oliphant’s Miss Marjoribanks (1866), and George Eliot’s Daniel Deronda (1876) all feature female heroines whose small actions drive their respective novels but have proven confounding to critics. I argue that these actions demonstrate meaningful agency despite—and really because of—the conventionality for which they have often been dismissed. Reconsidering these actions enlarges our understanding of female agency and its role in the nineteenth-century novel. In Good Girls: Female Agency and Convention in the Nineteenth-Century British Novel, I analyze how female characters adhere to standards of acceptable behavior in one area to evade restrictions in another. I refer to this strategy as conventional agency. Through their conventional actions, women exercise positive freedom, overcoming constraints to act. Conventional agency reshapes not only possibilities for female behavior but also the form of the novel. Novels that highlight such actions eschew melodrama and, to a certain extent, plot itself to focus on the minor and quotidian. Narrative innovations like episodic structures and anticlimactic endings emphasize this focus on small individual actions rather than plotting. Such features have often been read as flaws, but I reread them as meaningful aesthetic choices.
Contributors: Dong, Ge, Bhattacharjee, Amitava, Astrophysical Sciences—Plasma Physics Program Department
... Kinetic ballooning modes (KBM) are widely believed to play a critical role in explosive and disruptive dynamics in laboratory and space plasmas. While the nonlinear evolution of ballooning modes has been proposed as a mechanism for the eruptive events in the tokamak edge, known as edge localized modes (ELMs), and magnetospheric substorms, the role of kinetic effects in such nonlinear dynamics with potentially impulsive behavior remains largely unexplored. Detailed studies of the KBM nonlinear dynamics can help in understanding the cause and properties of the eruptive behavior and large turbulent transport in ELMs, and potentially contribute in our ability to predict and even control them in experiments. In this thesis nonlinear dynamics and saturation mechanism of KBM are presented using primarily global gyrokinetic particle-in-cell simulation results. The compressional component of magnetic perturbation δB∥ can be important for KBM in high β plasmas. A numerical scheme that includes δB∥ in first-principles gyrokinetic simulations has been formulated, implemented and benchmarked as a first step. With the perturbed electrostatic potential, and both the perpendicular and the parallel magnetic perturbations, KBM nonlinear evolution is studied for the Cyclone Base Case (CBC) parameters. In contrast to the finite-time singularity predicted by ideal MHD theory, the kinetic instability is shown to develop into an intermediate nonlinear regime of exponential growth, followed by a nonlinear saturation regulated by spontaneously generated zonal fields. The zonal fields, including both the zonal flow (flux-surface averaged electrostatic potential) and the zonal current (flux-surface averaged parallel vector potential), are shown to be important in governing the nonlinear mode structure, and in suppressing trans- port. The kinetic intermediate nonlinear regime resembles the intermediate regime already discovered in the full MHD simulations. During this regime, rapid growth of localized current sheet, which can induce tearing mode and magnetic reconnection, is observed. In the KBM simulations using experimentally measured equilibrium at the DIII-D tokamak edge, the nonlinear convective motion appears to compete with the shearing effect produced by zonal fields, which is weaker in the narrow pedestal steep gradient region compared with that in the core plasma. The effects of the zonal fields and the nonlinear non-zonal convection together regulate the KBM nonlinear saturation level in the DIII-D steep gradient region.
Contributors: Ko, Hsin-Yu, Car, Roberto, Chemistry Department
... Hybrid density functional theory (DFT) is widely used to obtain a semi-quantitative understanding of the electronic structures of isolated molecular clusters; however, it has limited applicability to large molecules and complex condensed-phase materials due to its high computational cost. To overcome this difficulty, a linear-scaling algorithm based on maximally localized Wannier functions (MLWF) can be employed. In the first part of this thesis, we present a detailed discussion on the theory, real-space implementation, and performance of this algorithm for enabling large-scale condensed-phase hybrid DFT based ab initio molecular dynamics (AIMD) simulations under realistic isobaric-isothermal (NpT) conditions. For the theory aspect, we discuss how the MLWF-based linear-scaling approach can be integrated into the Car-Parrinello AIMD framework. For our implementation (named exx module), we introduced several features to enable massive parallelization using hybrid MPI/OpenMP technologies, including custom data distribution scheme for MLWFs, static load balancing algorithm, and reusable proto-subdomains to exploit the localization in MLWF representation. Based on performance test using realistic condensed-phase liquid water systems (H2O)64, (H2O)128, and (H2O)256, we find the exx module to be quite efficient and scalable, hence making a hybrid DFT based AIMD simulation feasible. In the second part, we apply the exx module to study molecular crystals and liquids. The first application is to simulate the ice Ih, II, and III phases using AIMD at the dispersion-inclusive hybrid DFT level at their experimental triple point (238 K, 2.1 kbar). In the second application, we exploit the computational efficiency and scalability of our exx module in conjunction with leadership level supercomputers to perform path-integral AIMD (PI-AIMD) simulations on liquid water (300 K) and ice Ih (273 K) both under ambient pressure (1.0 bar) at dispersion-inclusive hybrid DFT level. We identify this level of theory provides a quite accurate description to water. From the resulting trajectory, we also find that the nuclear quantum fluctuation with autoprotolysis-type distortion promotes orbital localization. In the third application, we explore how anharmonicity, nuclear quantum effects (NQE), many-body dispersion interactions, and Pauli repulsion influence thermal properties of dispersion-bound molecular crystals using pyridine and similar organic molecular crystals.
Contributors: Vannucchi, Federica, Allais, Lucia, Architecture Department
... This dissertation traces the reform of architecture as a discipline in postwar Italy by examining one particular public institution in which architecture, its theorists, and its designers, directly confronted both public and political power: the Milan Triennale (officially known as the International Exhibition of Decorative Arts and Modern Architecture). In the 1960s and early 1970s, the dissertation argues, the Milan Triennale functioned as a “disciplinary mechanism,” that is, as a laboratory and testing ground for reshaping the relationship of architecture in both its theoretical and practical dimensions to politics. This relationship to power is examined through the lens of the tension between ideas presented at the exhibition and the nature of the Milanese institution as both executor of government resolutions and agent of the public’s will. Against the backdrop of Italy’s first abrupt period of economic unrest after World War Two, an interruption in the politics of centrismo (the center-right coalition that dominated Italy from 1947 to 1962), uprisings by students and workers, and the onset of a new era of reformism, the curators of three seminal exhibitions tested architecture as a means of political resistance against power and thereby refused to comply with the long-standing alliance between the Milan Triennale and the government. The exhibitions Tempo libero (Leisure) (1964) curated by Umberto Eco and Vittorio Gregotti, Grande numero (Greater Number) (1968) curated by Giancarlo De Carlo, and Architettura-città (Architecture-City) (1973) curated by Aldo Rossi led to a new understanding of architecture as a discipline that existed both “within and against” political power, to borrow an expression coined by neo-Marxist philosopher Mario Tronti. This dissertation follows the struggles of architects and critics as they operated “within” an institutional setting that was to endow their ideas with greater power, but also declared themselves as being “against” this very power structure.
Contributors: Koos, Joseph Douglas, Link, Aaron J, Molecular Biology Department
... Lasso peptides are a class of small molecules characterized by a unique threaded structure. In addition to this shape, lasso peptides are also of interest due to their range of properties, ranging from narrow spectrum anti-microbial to inhibiting viral envelope fusion. In recent years, with the increase in genomes available, it has become apparent that lasso peptides are present in a wider range of bacteria than had been identified through traditional natural products screening. In Chapters 2, a gene cluster containing two lasso peptides from the freshwater bacterium Asticcacaulis excentricus was examined to learn more about the promiscuity of lasso peptide related enzymes. The gene cluster contained a novel enzyme, termed a lasso isopeptidase, which can turn lasso peptides into a linear form. Using alanine scanning of the precursor peptides, it was determined that both the maturation enzymes as well as the isopeptidase were able to process a range of substrates. In Chapter 3, the structure of the isopeptidase enzyme was solved with and without precursor to learn more about how it recognized its substrates. In addition, the isopeptidase sequence was used to identify novel lasso peptide gene clusters, further expanding the known examples for this class. In Chapter 4, a novel lasso peptide gene cluster from Thermobifida fusca, a thermophilic bacterium, was identified as a source of soluble maturation enzymes for lasso peptide biosynthesis. The product was produced both through heterologous expression in E. coli, as well as by incubation of the precursor peptide with the maturation enzymes in vitro. This system was used to determine for the first time information about lasso peptide biosynthetic rates. In Chapter 5, a lasso peptide gene cluster was identified from Thermobifida cellulosilytica with a previously unidentified O-methyltransferase within the cluster. In addition, a similar enzyme was also identified within an unexplored class of products called actinopeptides. Each of these systems was explored through a combination of heterologous expression and in vitro experiments. Through the course of these studies, lasso peptide biosynthesis and degradation are on a more solid foundation for future examination.
The mechanical basis of Myxococcus xanthus self-organization and motility: from single cells to collective behavior
Contributors: Liu, Guannan, Shaevitz, Joshua W, Physics Department
... Many living organisms exhibit complicated but highly organized collective behaviors. Unlike passive systems whose dynamics are driven by thermal energy, living organisms are often active systems, in which motilities of individuals put the system far away from equilibrium. Naturally living in soil, social bacteria Myxococcus xanthus exhibits a series of fascinating self-organizing behaviors throughout its developmental cycle, including swarming during vegetative growth, forming rippling waves during predation, and aggregating into fruiting bodies when starved. In this thesis, I use M. xanthus as a model system and explore the mechanical basis behind its motility and self-organization. My work emphasizes on the utilization of microscopy, image processing techniques and data-driven analysis in the examination of M. xanthus on different scales. We first study M. xanthus fruiting body formation based on the statistical physics of active populations. We show that the aggregation process in M. xanthus resembles the dynamics of a spinodal decomposition phase separation. Modeling M. xanthus as active brownian particles, we demonstrate that the phase separation can be understood in terms of cell density and the Peclet number that captures the cell motility regarding its speed and reversal frequency. M. xanthus cells actively take advantage of their cellular control of motility to drive large scale aggregation by promoting gliding speed and suppressing reversals to increase motility persistence. Then we characterize the rippling behavior of M. xanthus both on single cell motility level and on population level. We find tracking data of single cells during rippling lacks the evidence to support the cell motion synchronization hypothesis. Using two different image processing techniques, we are able to characterize low density rippling structures by estimating local cell density. We further examine the high density rippling wave structures using a 3D laser microscope. Finally, we study the force generation mechanism of two distinct motility systems in M. xanthus. We find that cells use these motility systems in coordination while in groups. These results not only provided further understandings of the scale of forces M. xanthus experiences and exerts, but also suggests that M. xanthus mainly utilizes gliding motility during group migration.