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Nanophotonic Application to Biomedical Devices
Get PDFNanophotonics is the study of interactions between nanoscale structures and light. It has greatly expanded the fields of application over the past decades, taking advantage of the advancement in MEMS technology. The most common nanophotonic structures consist of either dielectrics, metals, or both. When a nanophotonic structure contains metals, it is considered as a plasmonic structure. Plasmonics is a field of light-metal interactions. Due to the negative permittivity of metals, the electromagnetic energy of light is focused at the metal-dielectric interface and creates plasmons-a collective motion of electrons in the conduction band of metals. By shaping metals into different structures to achieve a desired performance, plasmonics have been successfully applied to many fields including photovoltaics, spectroscopy, and biomedical devices.
This thesis provides 3 different applications of biomedical devices in which nanophotonics-articularly plasmonics-was applied. Chapter 1 discusses the application of nanophotonics to molecular sensing. In this chapter, an open-top, tapered waveguide that serves as a 3-dimensional plasmon cavity is demonstrated and achieves a near or single molecular detection. Chapter 2 discusses the application of nanophotonics to an implantable intraocular pressure sensor. In this chapter, an array of gold nanodots are introduced on a flexible membrane to optimize the performance of the sensor. Chapter 3 discusses the application of nanophotonics to angle-and-polarization independent pressure or strain sensing, which reduces the need for precise alignment or a trained technician, and therefore can be easily applied to moving subjects in diverse environments. Inspired by the geometry and optical principles of butterfly corneas, an array of gold paraboloids is designed to support a surface plasmon resonance that is angle-and-polarization independent. This array is integrated onto a hermetically sealed cavity with a flexible membrane and enables angle-and-polarization independent pressure/strain sensing.</p
Synthesis, Characterization, and Reactivity of Iron Hydrides in Nitrogen Fixation and Proton Coupled Electron Transfer from C-H bonds
Get PDFMitigating the hydrogen evolution (HER) is an outstanding challenge in small molecule reduction catalysis using protons and electrons. Nitrogen fixation is a fundamental reaction where this selectivity is of great importance. This thesis details mechanistic studies into the nitrogen fixation reaction and factors that contribute to hydrogen evolution. In addition to the mechanistic studies, the development of reagents with weak X-H bonds, with applications in N-H bond formation is presented. Chapter 1 presents a brief overview of catalytic nitrogen fixation, the role of hydride ligands, and the importance of reagents required for the formation of weak N-H bonds. Chapter 2 details the mechanism of photo-enhanced iron mediated N2 fixation. It is shown that off-path iron complexes bearing hydride ligands play an active role in hydrogen evolution by N2 fixation catalysts. The data presented lends further insight into the selectivity, activity, and required driving force relevant to iron (and other) N2RR catalysts. The third chapter describes the synthesis and characterization of a highly reactive iron(III) nitrido complex, a proposed key intermediate in nitrogen fixation mediated by [(P3B)Fe]+. The ability to synthesize and characterize such an intermediate provides additional support for a distal catalytic cycle for this catalyst. In Chapters 4 and 5, the reactivity of iron hydrides and their role as precursors towards weak C-H bonds is discussed. These chapters outline a valuable approach for the differentiation of a ring- versus a metal bound H-atom. Chapter 4 provides a structural, thermochemical, and mechanistic foundation for the characterization of ring protonated indene-based ligands with remarkably weak C-H bonds. Chapter 5 extends the characterization of such reactive species and presents ligand induced migration of the hydride to a Cp* ring.</p
Transport and Microrheology of Active Colloids
Get PDFActive colloids are micron-sized particles that self-propel through viscous fluids by converting energy extracted from their environment into mechanical motion. The origin or mechanism of their locomotion can be either biological or synthetic ranging from motile bacteria to artificial phoretic particles. Owing to their ability to self-propel, active colloids are out of thermodynamic equilibrium and exhibit interesting macroscopic or collective dynamics. In particular, active colloids exhibit accumulation at confining boundaries, upstream swimming in Poiseuille flow, and a reduced or negative apparent shear viscosity. My work has been focused on a theoretical and computational understanding of the dynamics of active colloids under the influence of confinement and external fluid flows, which are ubiquitous in biological processes. I consider the transport of active colloids in channel flows, the microrheology of active colloids, and lastly I propose and study a vesicle propulsion system based on the learned principles.
A generalized Taylor dispersion theory is developed to study the transport of active colloids in channel flows. I show that the often-observed upstream swimming can be explained by the biased upstream reorientation due to the flow vorticity. The longitudinal dispersion of active colloids includes the classical shear-enhanced dispersion and an active swim diffusivity. Their coupling results in a non-monotonic variation of the dispersivity as a function of the flow speed. To understand the effect of particle shape on the transport of active colloids, a simulation algorithm is developed that is able to faithfully resolve the inelastic collision between an ellipsoidal particle and the channel walls. I show that the collision-induced rotation for active ellipsoids can suppress upstream swimming. I then investigate the particle-tracking microrheology of active colloids. I show that active colloids exhibit a swim-thinning microrheology and a negative microviscosity can be observed when certain hydrodynamic effects are considered. I show that the traditional constant-velocity probe model is not suitable for the quantification of fluctuations in the suspension. To resolve this difficulty, a generalized microrheology model that closely mimics the experimental setup is developed. I conclude by proposing a microscale propulsion system in which active colloids are encapsulated in a vesicle with a semi-permeable membrane that allows water to pass through. By maintaining an asymmetric number density distribution, I show that the vesicle can self-propel through the surrounding viscous fluid.</p
Energy-Efficient Receiver Design for High-Speed Interconnects
Get PDFHigh-speed interconnects are of vital importance to the operation of high-performance computing and communication systems, determining the ultimate bandwidth or data rates at which the information can be exchanged. Optical interconnects and the employment of high-order modulation formats are considered as the solutions to fulfilling the envisioned speed and power efficiency of future interconnects. One common key factor in bringing the success is the availability of energy-efficient receivers with superior sensitivity. To enhance the receiver sensitivity, improvement in the signal-to-noise ratio (SNR) of the front-end circuits, or equalization that mitigates the detrimental inter-symbol interference (ISI) is required. In this dissertation, architectural and circuit-level energy-efficient techniques serving these goals are presented.
First, an avalanche photodetector (APD)-based optical receiver is described, which utilizes non-return-to-zero (NRZ) modulation and is applicable to burst-mode operation. For the purposes of improving the overall optical link energy efficiency as well as the link bandwidth, this optical receiver is designed to achieve high sensitivity and high reconfiguration speed. The high sensitivity is enabled by optimizing the SNR at the front-end through adjusting the APD responsivity via its reverse bias voltage, along with the incorporation of 2-tap feedforward equalization (FFE) and 2-tap decision feedback equalization (DFE) implemented in current-integrating fashion. The high reconfiguration speed is empowered by the proposed integrating dc and amplitude comparators, which eliminate the RC settling time constraints. The receiver circuits, excluding the APD die, are fabricated in 28-nm CMOS technology. The optical receiver achieves bit-error-rate (BER) better than 1E−12 at −16-dBm optical modulation amplitude (OMA), 2.24-ns reconfiguration time with 5-dB dynamic range, and 1.37-pJ/b energy efficiency at 25 Gb/s.
Second, a 4-level pulse amplitude modulation (PAM4) wireline receiver is described, which incorporates continuous time linear equalizers (CTLEs) and a 2-tap direct DFE dedicated to the compensation for the first and second post-cursor ISI. The direct DFE in a PAM4 receiver (PAM4-DFE) is made possible by the proposed CMOS track-and-regenerate slicer. This proposed slicer offers rail-to-rail digital feedback signals with significantly improved clock-to-Q delay performance. The reduced slicer delay relaxes the settling time constraint of the summer circuits and allows the stringent DFE timing constraint to be satisfied. With the availability of a direct DFE employing the proposed slicer, inductor-based bandwidth enhancement and loop-unrolling techniques, which can be power/area intensive, are not required. Fabricated in 28-nm CMOS technology, the PAM4 receiver achieves BER better than 1E−12 and 1.1-pJ/b energy efficiency at 60 Gb/s, measured over a channel with 8.2-dB loss at Nyquist frequency.
Third, digital neural-network-enhanced FFEs (NN-FFEs) for PAM4 analog-to-digital converter (ADC)-based optical interconnects are described. The proposed NN-FFEs employ a custom learnable piecewise linear (PWL) activation function to tackle the nonlinearities with short memory lengths. In contrast to the conventional Volterra equalizers where multipliers are utilized to generate the nonlinear terms, the proposed NN-FFEs leverage the custom PWL activation function for nonlinear operations and reduce the required number of multipliers, thereby improving the area and power efficiencies. Applications in the optical interconnects based on micro-ring modulators (MRMs) are demonstrated with simulation results of 50-Gb/s and 100-Gb/s links adopting PAM4 signaling. The proposed NN-FFEs and the conventional Volterra equalizers are synthesized with the standard-cell libraries in a commercial 28-nm CMOS technology, and their power consumptions and performance are compared. Better than 37% lower power overhead can be achieved by employing the proposed NN-FFEs, in comparison with the Volterra equalizer that leads to similar improvement in the symbol-error-rate (SER) performance.</p
Molecular Simulations of Charge Transport for Energy Storage and Conversion Applications
Get PDFMolecular simulation plays a variety of roles in accelerating the development of energy materials, from providing a fundamental understanding of molecular processes to predicting their performance spanning a wide range of chemical space. In this thesis, we present molecular simulation studies of charge transport both in bulk energy materials and at their interfaces to provide molecular principles for advanced rechargeable batteries in part I and electricity generation using a metal nanofilm from water motion in part II.
In part I, we discuss ion transport and interfacial electron transfer in polymeric battery materials, both of which are closely associated with battery operation. As a bulk electrolyte and a solid electrolyte interphase (SEI), polymeric materials often benefit rechargeable batteries, allowing for enhanced safety and increased energy density. Firstly, we propose a unique mechanism of lithium-ion transport in polymer-based electrolytes, including conjugated polymers with an imidazolium sidechain and polyborane-based single-ion conductors, which utilizes the formation of a percolating ion network to facilitate lithium ion transport. Secondly, we discuss interfacial ion solvation structure and dynamics that are closely related to interfacial electron-transfer kinetics. Simulations provide molecular insights into how a functional SEI passivates a metal electrode, thereby accelerating materials discovery such as an artificial SEI of self-assembled monolayers.
In part II, we present molecular principles of energy conversion from a flow of ionic solution to electricity using metal nanolayers. The energy conversion emerges at a water-solid interface and requires a boundary of an electrical double layer at which ion adsorption and desorption occur along with the flow. We discuss charge induction mechanisms related to a heterolayered structure of a metal nanolayer and investigate factors that affect energy conversion efficiency in two different modes of operation, namely a flow cell and a wavetank.</p
The Modular Synthesis and Functionalization of Cyclic Compounds Using Modern Methods
Get PDFAccessing libraries of similar compounds quickly is important in the pharmaceutical industry, as it allows for the expedient investigation of a wide variety of parameters. An efficient strategy to access compounds of interest is to start from a single intermediate containing an interesting or pharmaceutically active structure and decorating it with varying functionality to generate a library of related compounds. Cross-coupling is a powerful tool for this type of divergent, modular approach.
Herein, we discuss several strategies geared towards the synthesis of small libraries of compounds of interest. First, a modular approach towards a library of enantioenriched trans cyclobutanes is discussed. This strategy allows for the synthesis of diverse substrates from a single enantioenriched intermediate, and this approach was applied to the synthesis of the small molecule (+)-rumphellaone A. Finally, the development of an enantioselective nickel-catalyzed photoredox cross-coupling to form N-(hetero)benzylic azoles in collaboration with researchers at Merck is discussed.</p
Machine Learning and Modeling Methods for Protein Engineering
Get PDFComputation has been an integral part of structural biology, ever since the first protein macromolecular structure was solved via Fourier Synthesis on the EDSAC Mark I electronic computer in 1958 (Kendrew et al., 1958). Throughout my time at Caltech, I have endeavored to develop new methods to apply machine learning and molecular modeling to the study of biological macromolecules. These efforts have taken two distinct tracks, but are unified by a focus on studying proteins on a structural level.
Through the application of molecular dynamics and modeling, I have studied insulin from several angles, including the incorporation of non-canonical amino acids, and how these modifications might be responsible for the modification of critical properties such as hexamer dissociation and fibrillation formation. Additionally, I have probed how insulin behaves at the interface of water and silica, a property which is critical for the effective dissemination and administration of this therapeutic molecule. I have helped to develop a novel computationally guided workflow for integrating drug conjugates into antibody CDRs. This technique yields molecules which exhibit synergistic binding and an enhanced ability for selective binding.
The second major thrust of my research has focused on applying machine learning to protein engineering problems, particularly developing tools for working with structural data, and for making efficient re-use of data which has already been laboriously collected by other groups. The basic data parsing and processing tools which were created and refined over the course of my time at Caltech has enabled many other projects, both of my own and of collaborators. Studies into the use of generative networks for protein-protein docking have been conducted which lend useful insights for network architecture, the inclusion of intermediate learning objectives, and overcoming sparsity. The technique introduced in our ICLR 2021 paper demonstrates a regularization method which enables data from past protein engineering campaigns to be leveraged to learn policies which optimally select molecules to synthesize in unrelated engineering efforts, to potentially save a significant amount of time and money for future projects.
Reference
Kendrew, J. C.; Bodo, G.; Dintzis, H. M.; Parrish, R. G.; Wyckoff, H.; Phillips, D. C. A. "Three-Dimensional Model of the Myoglobin Molecule Obtained by X-Ray Analysis". Nature 1958, 181 (4610), 662–666.</p
Gas Planet Seismology and Cooling
Get PDFIn this thesis I advocate for the enhancement of interdisciplinary expertise between atmospheric and interiors sciences. I illustrate the intimate connection between atmosphere and interior with four projects involving two major topics: giant planet seismology, and convective inhibition by condensation. First I advance a heuristic to evaluate generic localized excitation sources for giant planet seismicity, concluding observed oscillations on Jupiter may be caused by highly energetic rock storms lurking deep beneath the visible clouds. Next I develop a method to use existing spacecraft data to probe for seismic activity on giant planets, applying the method to Cassini data. This method finds possible evidence of p-modes on Saturn, excited to staggering amplitudes warping the surface of Saturn with kilometer scale displacements. Next I explore the impact of convective inhibition on Uranus and Neptune, finding that condensation of methane and water produces non-negligible corrections to these planets' thermal histories. Finally I explore a similar mechanism operating in the limit where condensing species are highly abundant. I find that considering convective inhibition, super-Earths can retain their primordial heat for longer than the age of the universe.</p
Quantum Constructions on Hamiltonians, Codes, and Circuits
Get PDFThis thesis covers three different and largely unrelated projects from my time as a Ph.D. student studying quantum information and computation.
In the first chapter, we construct a Hamiltonian whose dynamics simulate the dynamics of every other Hamiltonian up to exponentially long times in the system size. The Hamiltonian is time independent, local, one dimensional, and translation invariant. As a consequence, we show (under plausible computational complexity assumptions) that the circuit complexity of the unitary dynamics under this Hamiltonian grows steadily with time up to an exponential value in system size. This result makes progress on a recent conjecture by Susskind, in the context of the AdS/CFT correspondence, that the time evolution of the thermofield double state of two conformal field theories with a holographic dual has circuit complexity increasing linearly in time, up to exponential time.
In the second chapter, we study approximate quantum low-density parity-check (QLDPC) codes, which are approximate quantum error-correcting codes specified as the ground space of a frustration-free local Hamiltonian, whose terms do not necessarily commute. Such codes generalize stabilizer QLDPC codes, which are exact quantum error-correcting codes with sparse, low-weight stabilizer generators (i.e. each stabilizer generator acts on a few qubits, and each qubit participates in a few stabilizer generators). Our investigation is motivated by an important question in Hamiltonian complexity and quantum coding theory: do stabilizer QLDPC codes with constant rate, linear distance, and constant-weight stabilizers exist?
We show that obtaining such optimal scaling of parameters (modulo polylogarithmic corrections) is possible if we go beyond stabilizer codes: we prove the existence of a family of [[N, k, d, ε]] approximate QLDPC codes that encode k = Ω̃(N) logical qubits into N physical qubits with distance d = Ω̃(N) and approximation infidelity ε = ℴ(1/polylog(N)). The code space is stabilized by a set of 10-local noncommuting projectors, with each physical qubit only participating in ℴ(polylogN) projectors. We prove the existence of an efficient encoding map and show that the spectral gap of the code Hamiltonian scales as Ω̃(N-3.09). We also show that arbitrary Pauli errors can be locally detected by circuits of polylogarithmic depth.
Our family of approximate QLDPC codes is based on applying a recent connection between circuit Hamiltonians and approximate quantum codes (Nirkhe, et al., ICALP 2018) to a result showing that random Clifford circuits of polylogarithmic depth yield asymptotically good quantum codes (Brown and Fawzi, ISIT 2013). Then, in order to obtain a code with sparse checks and strong detection of local errors, we use a spacetime circuit Hamiltonian construction in order to take advantage of the parallelism of the Brown-Fawzi circuits.
The analysis of the spectral gap of the code Hamiltonian is the main technical contribution of this work. We show that for any depth D quantum circuit on n qubits there is an associated spacetime circuit-to-Hamiltonian construction with spectral gap Ω(n-3.09D-2log-6(n)). To lower bound this gap we use a Markov chain decomposition method to divide the state space of partially completed circuit configurations into overlapping subsets corresponding to uniform circuit segments of depth log n, which are based on bitonic sorting circuits. We use the combinatorial properties of these circuit configurations to show rapid mixing between the subsets, and within the subsets we develop a novel isomorphism between the local update Markov chain on bitonic circuit configurations and the edge-flip Markov chain on equal-area dyadic tilings, whose mixing time was recently shown to be polynomial (Cannon, Levin, and Stauffer, RANDOM 2017). Previous lower bounds on the spectral gap of spacetime circuit Hamiltonians have all been based on a connection to exactly solvable quantum spin chains and applied only to 1+1 dimensional nearest-neighbor quantum circuits with at least linear depth.
In the third and final chapter, we study the problem of maximum-likelihood (ML) decoding of stabilizer codes under circuit level noise. As progress in the design of proposed fault-tolerant quantum computing architectures moves forward, it is becoming essential to achieve the highest noise suppression possible from the underlying quantum error correcting code. The decoder, which ultimately decides which correction to apply to an encoded state that has suffered an error, is an essential part of this design. So-called maximum likelihood decoders achieve optimal error suppression, but using such a decoder becomes intractable as the size of code grows, therefore sub-optimal decoders which achieve good performance and favorable implementation complexity are used instead. Circuit level noise presents a particular challenge for achieving good performance and practical complexity. We present the construction of a subsystem code called the Circuit History Code which provides an algebraic structure for understanding and classifying circuit level errors. We use this structure to formulate maximum likelihood decoding under circuit level noise as a tensor network contraction. This in turn allows the implementation of approximate maximum likelihood decoders which we expect could provide near optimal decoding performance with considerably lower complexity. Using tensor network ML decoders can be useful for benchmarking the performance of efficient decoders being designed for implementation in real experiments, as well as providing options for implementing decoders for codes that would be difficult to decode with conventional methods.</p
From Building Blocks to Theories: EFThedron and a Haagerup TFT
Get PDFThis thesis is dedicated to the study of certain building blocks of scattering amplitudes in (3+1)d Minkowskian spacetime and that of topological field theory in (1+1)d, together with the constraints which result from the properties of these building blocks.
The first part of the thesis is concerned with the introduction of an on-shell formalism for massless and massive particles. We identify all possible three-point tensor structures compatible with the little group symmetry and overall mass dimension, and use them to arrive at a new description of various scattering amplitudes through unitarity and locality. One of the objects that result from this construction, the spinning polynomial, is then fed into the dispersion relation to derive a convex hull constraining the EFT coefficients. We further investigate the intersection of the convex hull resulting from the positive expansion of residue and the half moment curve.
In the second part, we turn our attention to topological defect lines in (1+1)d topological field theory with Haagerup fusion ring. We first solve for the F-symbols of fusion categories in the Haagerup-Izumi family under the assumption of transparency. The purpose of transparency is twofold: it allows for a simple formula for F-symbols while at the same time tremendously simplifies the diagrammatic calculus with topological defect lines. Finally, we construct a topological field theory with 15 pointlike operators and demonstrate that it satisfies the four-point crossing constraints and torus one-point modular invariance constraints.</p