Design Space Extrapolation and Inverse Design using Machine Learning

Modern electronic systems need to be analyzed and designed carefully for their operation at higher frequencies and many control parameters. This process takes up a huge time for computations and design cycles. To this effect, in this webinar, we investigate machine learning techniques for power delivery, signal integrity and EM problems. More specifically, we present two broad design strategies. Often one needs to predict the structure behavior outside the range of simulations. This work deals with extrapolation in two domains. (1) We propose HilbertNet for complex-valued causal extrapolation of frequency responses. The proposed architecture accurately predicts the out-of-band frequency response by modelling the temporal correlations between in-band frequency samples using specialized recurrent neural networks. (2) We propose Transposed Convolutional Networks to model spatial correlations in the design space. The design space comprises of all the geometrical and material parameters characterizing the response. The convolutional networks can extrapolate the design space in as high as 11 dimensions because of inducing spatial bias into the model. These techniques constitute forward design. We also present some recent methods developed for inverse design of electronic systems. The goal in inverse design is to estimate the best set of design space values that generate the response space. We employ invertible neural networks to model the non-linear mapping between the design space and the response space. We show the effectiveness of these techniques in signal and power integrity applications.Ph.D

Development of new approaches for characterising DNA origami-based nanostructures with atomic force microscopy and super-resolution microscopy

DNA nanotechnology has developed a versatile set of methods to utilise DNA self-assembly for the bottom-up construction of arbitrary two- and three-dimensional DNA objects in the nanometre size range, and to functionalise the structures with unprecedented site-specificity with nanoscale objects such as metallic and semiconductor nanoparticles, proteins, fluorescent dyes, or synthetic polymers. The advances in structure assembly have resulted in the application of functional DNA-based nanostructures in a gamut of fields from nanoelectronic circuitry, nanophotonics, sensing, drug delivery, to the use as host structure or calibration standard for different types of microscopy. However, the analytical means for characterising DNA-based nanostructures drag behind these advances. Open questions remain, amongst others in quantitative single-structure evaluation. While techniques such as atomic force microscopy (AFM) or transmission electron microscopy (TEM) offer feature resolution in the range of few nanometres, the number of evaluated structures is often limited by the time-consuming manual data analysis. This thesis has introduced two new approaches to quantitative structure evaluation using AFM and super-resolution fluorescence microscopy (SRM). To obtain quantitative data, semi-automated computational image analysis routines were tailored in both approaches. AFM was used to quantify the attachment yield and placement accuracy of poly(3-tri(ethylene glycol)thiophene)-b-oligodeoxynucleotide diblock copolymers on a rectangular DNA origami. This work has also introduced the first hybrid of DNA origami and a conjugated polymer that uses a highly defined polythiophene derivative synthesised via state-of-the-art Kumada catalyst-transfer polycondensation. Among the AFM-based studies on polymer-origami-hybrids, this was the first to attempt near-single molecule resolution, and the first to introduce computational image analysis. Using the FindFoci tool of the software ImageJ revealed attachment yields per handle between 26 - 33%, and determined a single block copolymer position with a precision of 80 - 90%. The analysis has pointed out parameters that potentially influence the attachment yield such as the handle density and already attached objects. Furthermore, it has suggested interactions between the attached polymer molecules. The multicolour SRM approach used the principles of single-molecule high-resolution co-localisation (SHREC) to evaluate the structural integrity and the deposition side of the DNA origami frame “tPad” based on target distances and angles in a chiral fluorophore pattern the tPads were labelled with. The computatinal routine that was developed for image analysis utilised clustering to identify the patterns in a sample’s signals and to determine their characteristic distances and angles for hundreds of tPads simultaneously. The method excluded noise robustly, and depicted the moderate proportion of intact tPads in the samples correctly. With a registration error in the range of 10 -15 nm after mapping of the colour channels, the precision of a single distance measurements on the origami appeared in the range of 20 - 30 nm. By broadening the scope of computational AFM image analysis and taking on a new SRM approach for structure analysis, this work has presented working approaches towards new tools for quantitative analysis in DNA nanotechnology. Furthermore, the work has presented a new approach to constructing hybrid structures from DNA origami and conjugated polymers, which will open up new possibilities in the construction of nanoelectronic and nanophotonic structures

Instrument design and optimization of interferometric reflectance imaging sensors for in vitro diagnostics

Thesis (Ph.D.)--Boston UniversityIn the field of drug discovery and disease diagnostics, protein microarrays have generated much enthusiasm for their high-throughput monitoring of biomarkers; however, this technology has yet to translate from research laboratories to commercialization. The hindrance is the considerable uncertainty and skepticism regarding data obtained. The disparity in results from different laboratories performing identical tests is attributed to a lack of assay quality control. Unlike DNA microarrays, protein microarrays have a higher level of bioreceptor immobilization variability and non-specific binding because of the more complex molecular structure and broader physiochemical properties. Traditional assay detection modalities, such as fluorescence microscopy and surface plasmon resonance, are unable to overcome both of these sources of variation. This dissertation describes the hardware and software design and biological validation of three complementary platforms that overcome bioreceptor variability and non-specific binding for diagnostics. In order to quantify the bioreceptor quality, a label-free, nondestructive, low cost, and high-throughput interferometric sensor has been developed as a quality control tool. The quality control tool was combined with a wide-field fluorescence imaging system to improve fluorescence experimental repeatability. Lastly, a novel high-throughput and label-free platform for quality control and specific protein microarray detection is described. This platform overcomes the additional complexities and time required with labeled assays by discriminating between specific and nonspecific detection by including sizing of individual binding events. Protein microarrays may one day emerge as routine clinical laboratory tests; however, it is important that the proper quality control procedures are in place to minimize erroneous results. These platforms provide reliable and repeatable protein microarray measurements for new advancements in disease diagnostics with the potential for drug discovery

Design and Synthesis of Efficient Circuits for Quantum Computers

Οι πρόσφατες εξελίξεις στον τομέα της πειραματικής κατασκευής κβαντικών υπολογιστών με εξαρτήματα αυξημένης αξιοπιστίας δείχνει ότι η κατασκευή τέτοιων μεγάλων μηχανών βασισμένων στις αρχές της κβαντικής φυσικής είναι πιθανή στο κοντινό μέλλον. Καθώς το μέγεθος των μελλοντικών κβαντικών υπολογιστών θα αυξάνεται, η σχεδίαση αποδοτικότερων κβαντικών κυκλωμάτων και μεθόδων σχεδίασης θα αποκτήσει σταδιακά πρακτικό ενδιαφέρον. Η συνεισφορά της διατριβής στην κατεύθυνση της σχεδίασης αποδοτικών κβαντικών κυκλωμάτων είναι διττή: Η πρώτη είναι η σχεδίαση καινοτόμων αποδοτικών αριθμητικών κβαντικών κυκλωμάτων βασισμένων στον Κβαντικό Μετασχηματισμό Fourier (QFT), όπως πολλαπλασιαστής-με-σταθερά-συσσωρευτής (MAC) και διαιρέτης με σταθερά, με γραμμικό βάθος (ή ταχύτητα) ως προς τον αριθμό ψηφίων των ακεραίων. Αυτά τα κυκλώματα συνδυάζονται αποτελεσματικά ώστε να επιτελέσουν την πράξη του modulo πολλαπλασιασμού με σταθερά με γραμμική πολυπλοκότητα χρόνου και χώρου και συνεπώς μπορούν να επιτελέσουν την πράξη της modulo εκθετικοποίησης (modular exponentiation) με τετραγωνική πολυπλοκότητα χρόνου και γραμμική πολυπλοκότητα χώρου. Οι πράξεις της modulo εκθετικοποίησης και του modulo πολλαπλασιασμού είναι αναπόσπαστα μέρη του σημαντικού κβαντικού αλγορίθμου παραγοντοποίησης του Shor, αλλά και άλλων κβαντικών αλγορίθμων της ίδιας οικογένειας, γνωστών ως κβαντική εκτίμηση φάσης (Quantum Phase Estimation). Αντιμετωπίζονται με αποτελεσματικό τρόπο σημαντικά προβλήματα υλοποίησης, που σχετίζονται με την απαίτηση χρήσης κβαντικών πυλών περιστροφής υψηλής ακρίβειας, καθώς και της χρήσης τοπικών επικοινωνιών. Η δεύτερη συνεισφορά της διατριβής είναι μία γενική μεθοδολογία ιεραρχικής σύνθεσης κβαντικών και αντιστρέψιμων κυκλωμάτων αυθαίρετης πολυπλοκότητας και μεγέθους. Η ιεραρχική μέθοδος σύνθεσης χειρίζεται καλύτερα μεγάλα κυκλώματα σε σχέση με τις επίπεδες μεθόδους σύνθεσης. Η προτεινόμενη μέθοδος προσφέρει πλεονεκτήματα σε σχέση με τις συνήθεις ιεραρχικές συνθέσεις που χρησιμοποιούν την μέθοδο "υπολογισμός-αντιγραφή-αντίστροφος υπολογισμός" του Bennett.The recent advances in the field of experimental construction of quantum computers with increased fidelity components shows that large-scale machines based on the principles of quantum physics are likely to be realized in the near future. As the size of the future quantum computers will be increased, efficient quantum circuits and design methods will gradually gain practical interest. The contribution of this thesis towards the design of efficient quantum circuits is two-fold. The first is the design of novel efficient quantum arithmetic circuits based on the Quantum Fourier Transform (QFT), like multiplier-with-constant-and-accumulator (MAC) and divider by constant, both of linear depth (or speed) with respect with the bits number of the integer operands. These circuits are effectively combined so as they can perform modular multiplication by constant in linear depth and space and consequently modular exponentiation in quadratic time and linear space. Modular exponentiation and modular multiplication operations are integral parts of the important quantum factorization algorithm of Shor and other quantum algorithms of the same family, known as Quantum Phase Estimation algorithms. Important implementation problems like the required high accuracy of the employed rotation quantum gates and the local communications between the gates are effectively addressed. The second contribution of this thesis is a generic hierarchical synthesis methodology for arbitrary complex and large quantum and reversible circuits. The methodology can handle more easily larger circuits relative to the flat synthesis methods. The proposed method offers advantages over the standard hierarchical synthesis which uses Bennett's method of "compute-copy-uncompute"

DEVELOPMENT OF NANO/MICROELECTROMECHANICAL SYSTEM (N/MEMS) SWITCHES

Ph.DDOCTOR OF PHILOSOPH

MEMS Accelerometers

Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc

Metal Nanoparticles-Polymer Hybrid Materials

Metal nanoparticles/polymers hybrid materials have significantly contributed to the develop of nanotechnology. Moreover, these hybrid materials can respond to stimuli (e.g., pH, temperature, light, magnetic field) or self-degrade in a controlled manner to release metal nanoparticles or therapeutics encapsulated. Functional and structural hybrid materials provide opportunities for creative fields, remarkable properties, and future advanced applications. This Special Issue focuses on highlighting the progress of new hybrid materials, based on metal nanoparticles and polymers, their design, preparation, functionalization, characterization, and advanced applications