ESE PhD Thesis Defense: "Chemical vapor deposition synthesis of graphene and transition metal dichalcogenides and their applications"
2023-07-05 10:00 (America/New_York) | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
2D materials is a rapidly expanding class of materials that have captivated academia and industry with their ultrathin nature and remarkable properties. Graphene, the first discovered material, shows exceptional mechanical strength and superior electrical properties, presenting exciting probabilities in many applications. Combined with its large surface area and biocompatibility, graphene is particularly promising for the development of highly sensitive and selective biosensors. However, the application of graphene is limited by its lack of a bandgap, making it unusable for advanced logic circuits. 2D materials beyond graphene are thus being explored. Transition metal dichalcogenides (TMDs) are representative candidates possessing a variety of properties including tunable bandgaps. Conventionally, both graphene and TMDs are produced by mechanical exfoliation, but this method is low-yield and not suitable for large-scale applications such as biosensing. Therefore, a reliable synthesis strategy for these materials is urgently needed. In this thesis, synthesis of graphene and TMDs by chemical vapor deposition (CVD) is explored. The CVD synthesized graphene sheet has monolayer structure which can be inch scale in size, enabling the scalable fabrication of graphene biosensors. We develop the fabrication process of graphene biosensors and explore their biosensing applications, where the sensors are used to study the interaction between a specially designed water-soluble mu opioid receptor (wsMOR) and G-protein. The biosensors are able to record the in vitro interaction between the two molecules with high sensitivity. The CVD growth of TMDs is also investigated. Rapid growth of inch-scale monolayer MoSe2 continuous film has been synthesized on insulating substrates, based on a spin-coating, NaCl assisted CVD approach. This approach is promising to be extended to the growth of other semiconducting TMDs, benefit to the batch production of large-area TMD electronics. Additionally, we studied the CVD synthesis of TMDs with controlled layer numbers at controlled locations. Various approaches are used to demonstrate the high quality of the materials and field-effect transistor measurements indicate their potential in making advanced electronic devices.

CBE PhD Thesis Defense: "Comparative analysis of aneuploidy in suspension cancer lines and solid tumors: insights from single cell sequencing approaches"
2023-07-06 10:00 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Aneuploidy, a cancer hallmark, has intrigued researchers due to its near-universal presence in cancer. However, studying its impact is challenging due to the involvement of numerous genes and the difficulty in creating suitable models. Advances in sequencing technology and the vast data available in the Cancer Genome Atlas (TCGA) enabled us to use the p53-null suspension cancer cell line, THP-1, as a model to explore genomic instability in hematopoietic cancer. We aimed to understand why non-adherent cancers typically exhibit lower aneuploidy levels compared to solid tumors. Through an examination of the spindle assembly checkpoint (SAC) and the application of physical and chemical perturbations, we discovered that suspension cancer lines displayed no discernible differences in SAC functionality or sensitivity to external perturbations compared to solid tumors. Notably, chemical perturbations led to the emergence of copy number variations (CNVs) that provided proliferative advantages to daughter cells. Introduction of p53 into THP-1 did not rescue aneuploidy levels, aligning with previous research suggesting its upstream role in suppressing aneuploidy. However, the introduction of p53 did restore downstream p21 pathways, which are known to suppress cancer cell proliferation. Interestingly, the expected growth suppression was found to be independent of p21 levels. Furthermore, the engineered THP-1 exhibited reduced p53 levels after treatment with reversine and etoposide, unlike adherent cancer cells. These findings indicate distinct p53 pathways in liquid cancer lines that ensure genomic integrity. For future CNV analysis, we introduced the live cell ChReporter, enabling non-invasive tracing of CNV status without compromising cell viability.

MEAM Ph.D. Thesis Defense: "Adding Actuation to Found Material: A Design Methodology"
2023-07-06 13:00 - 14:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Engineers in modern society are taught to design and build structures and robots from pre-processed materials, giving them the ability to describe the operating capacity of their structure with a high degree of certainty. From a disaster recovery and robust systems point of view, this is a severe limitation. Rather than use processed material of known mechanical properties, we investigate how to use ”found” material, or preexisting material located at the deployment site, to build and repair new and existing systems.
We begin by introducing a new design methodology for building with found materials. The methodology is compared with the standard engineering design process to identify the areas where a user must deviate from the standard practice. We investigate two of these deviations, focusing on material identification and designing with that material as well as actuator integration with the found materials. The work uses experimental results to validate the actuator integration, using both wood and ice as structural bases.
We review current research in the field of found materials and self-replication before presenting our work. Our contributions include a design methodology for using found material, techniques to design structures from found material, and actuator integration with ice and wood. We summarize these techniques through the construction of a variety of robots and structures including StickBot, a flexible robotic system; IceBot, a ground-based rover vehicle from ice; and an ice arm capable of cutting blocks of ice into arm segments for future use.

BE Doctoral Dissertation Defense: "In Situ and In Vivo Roles of Focal Adhesion Kinase in Tendon Development and Mechanotransduction" (Thomas Leahy)
2023-07-07 14:00 - 16:00 | CRB Auditorium, 415 Curie Boulevard, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Louis Soslowsky are pleased to announce the Doctoral Dissertation Defense of Thomas Leahy.

Title: “In Situ and In Vivo Roles of Focal Adhesion Kinase in Tendon Development and Mechanotransduction”

Date: July 7, 2023
Time: 2:00PM
Location: CRB Austrian Auditorium
Zoom link

The public is welcome to attend.

MEAM Ph.D. Thesis Defense: "Data-Driven Model Discovery for Non-Equilibrium Phenomena: Unraveling Continuum Behavior from Stochastic Dynamics"
2023-07-10 10:00 - 11:00 | Towne 307, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Non-equilibrium phenomena are ubiquitous across material systems and of great technological relevance. Examples of such phenomena include diffusion processes in liquid and gases, viscoelasticity and plasticity in solids, and rheological behavior of colloidal and granular media. Despite their ubiquity and importance, the understanding of non-equilibrium phenomena remains in its infancy compared with classical equilibrium thermodynamics and statistical mechanics from both theoretical and computational aspects. As a consequence, current modeling and simulation strategies, including multiscale paradigms, are mostly trapped within a compromise between computational efficiency and physical fidelity.
This thesis leverages recent advances in non-equilibrium physics, together with emerging machine learning techniques, to develop theoretical and computational paradigms for learning continuum evolution equations using data-driven methods. First, we present a new strategy for continuum model discovery that uses fluctuation theorems, particularly, the Jarzynski equality, to identify the reversible (elastic) and irreversible (dissipative) response. Second, we propose a machine learning architecture called Variational Onsager Neural Networks (VONNs) to learn thermodynamically consistent non-equilibrium evolution PDEs based on Onsager’s variational principle. Thirdly, we develop a multiscale machine learning framework called Statistical-Physics-Informed Neural Networks (Stat-PINNs) to uniquely determine coarse-grained dissipative evolution equations from stochastic particle dynamics by leveraging fluctuation-dissipation relations. Lastly, we introduce a statistical mechanics framework with quantified uncertainty to extrapolate material behavior to different loading conditions (including far-from-equilibrium conditions) or material systems.

ESE PhD Thesis Defense: "A Robot's Search for Meaning: Semantics as a Common Representation for Heterogeneous Robot State Estimation and Collaboration"
2023-07-10 12:30 - 14:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Mapping and navigation have gone hand-in-hand since long before robots existed. For almost as long, maps have also been a key form of communication, allowing someone who has never been to an area to nonetheless navigate that area successfully. In the context of multi-robot systems, the maps and information that flow between robots are what enables effective collaboration, whether those robots are operating simultaneously or years apart in time. In this thesis, we argue that maps must go beyond encoding purely geometric or color information in order to enable increasingly complex autonomy, particularly between robots. We propose systems for mapping and localization, showing that semantic maps can be an important end in themselves as well as a means to achieve improved global localization in a variety of contexts. We then build on these ideas and employ semantic maps to underly a framework for multi-robot autonomy, focusing in particular on air and ground robots. A distinguishing characteristic of this thesis is that we strongly emphasize field experiments and testing, and we demonstrate that these ideas can work at scale in the real world. We also perform extensive simulation experiments to validate our ideas at even larger scales. These experiments and systems constitute a step forward in large-scale, collaborative multi-robot systems operating with real communication, navigation, and perception constraints.

PSOC@Penn Seminar: Larry Dooling
2023-07-10 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

BE Doctoral Dissertation Defense: "The roles of YAP and TAZ in fetal bone development" (Joseph Collins)
2023-07-10 14:30 - 16:30 | CRB Auditorium, 415 Curie Boulevard, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Joel Boerckel are pleased to announce the Doctoral Dissertation Defense of Joseph Collins.

Title: The roles of YAP and TAZ in fetal bone development

Date: July 10, 2023
Time: 2:30pm
Location: CRB Austrian Auditorium

The public is welcome to attend.

Join Zoom Meeting
https://us02web.zoom.us/j/4136654254?pwd=[REDACTED]
Meeting ID: 413 665 4254
Passcode: [REDACTED]

MEAM Seminar: "Semantic Localization, Mapping, and Exploration by Multiple Aerial Robots"
2023-07-11 10:00 - 11:30 | Moore 212
Traditional approaches for active mapping focus on building geometric maps. For most real-world applications, however, actionable information is related to semantically meaningful objects in the environment. We propose an approach to the active metric-semantic mapping problem that enables multiple heterogeneous robots to collaboratively build a map of the environment. The robots actively explore to minimize the uncertainties in both semantic(object classification) and geometric (object modeling) information. We represent the environment using informative but sparse object models, each consisting of a basic shape and a semantic class label, and characterize uncertainties empirically using a large amount of real-world data. Given a prior map, we use this model to select actions for each robot to minimize uncertainties. The performance of our algorithm is demonstrated through multi-robot experiments in diverse real-world environments. The proposed framework is applicable to a wide range of real-world problems, such as precision agriculture, infrastructure inspection, and asset mapping in factories.

BE Doctoral Dissertation Defense: "Macrophages & chromosomal instability: From unraveling immunomodulatory interactions to effects of chromosomal instability on macrophage-mediated anti-tumor response" (Brandon Hayes)
2023-07-11 10:00 - 12:00 | Berger Auditorium (Room 13), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Dennis Discher are pleased to announce the Doctoral Dissertation Defense of Brandon Hayes.

Title: Macrophages & chromosomal instability: From unraveling immunomodulatory interactions to effects of chromosomal instability on macrophage-mediated anti-tumor response

Date: July 11, 2023
Time: 10:00am
Location: Berger Auditorium in Skirkanich

The public is welcome to attend.

Zoom option:
https://upenn.zoom.us/j/92480264650?pwd=[REDACTED]

Meeting ID: 924 8026 4650
Passcode: [REDACTED]

MEAM Ph.D. Thesis Defense: "Transport and Mixing with Swimming Microorganisms in Chaotic Flows"
2023-07-12 09:30 - 10:30 | Moore 212
Microorganisms, primitive unicellular forms of life, form the basis of the food web and play crucial roles in the Earth’s biogeochemical cycles. Habitats of microorganisms, from oceans and lakes to soil and human intestines, are often characterized by constant fluid motion. Fluid flow exerts forces and torques on microorganisms that affect their movement and distribution, and transports essential chemicals on which they rely for sensing, foraging, and mating. As a result, flow has a broad range of effects on the behaviors of microorganisms, including their locomotion, reproduction, nutrient uptake, and communication. Despite many efforts to understand microbiology in aquatic environments, it remains a challenge to interpret the physical and biological behaviors of microorganisms in the presence of fluid flows, particularly unsteady and chaotic flows.
In this thesis, I investigate the interaction between motile microorganisms and dynamical structures in chaotic flows, and the effects of such interaction on transport and mixing. The flow dynamical structures investigated here are known as the Lagrangian coherent structures (LCSs). First, I characterize the transport and mixing in a spatially periodic chaotic flow with swimming Escherichia coli. The microorganisms are found to align and accumulate near structures of strong stretching of fluid parcels, or namely, the hyperbolic LCSs. Such alignment and accumulation of microorganisms lead to reduction in large-scale transport but enhancement in small-scale mixing. Second, I examine the transport and mixing with E. coli in a more complex spatially aperiodic chaotic flow. The microorganisms are found to escape and deplete in vortex-like dynamical structures known as the elliptic LCSs. The depletion leads to enhanced transport barriers into which the transport of diffusive chemicals is much slower. Lastly, I investigate the mixing in the self-generated chaotic flows of swarming Serratia marcescens and show that dilute polymers can substantially enhance mixing induced by collective behaviors. Overall, this dissertation elucidates the nontrivial effects of the interaction between microorganisms and flow structures on transport and mixing.

ESE PhD Thesis Defense: "Discrete and Continuous Optimization for Collaborative and Multi-task Learning"
2023-07-14 11:00 - 13:00 | Room 452 C, 3401 Walnut, 3401 Walnut Street, Philadelphia, PA, 19104, United States
This thesis is dedicated to addressing the challenges of robust collaborative learning and optimization in both discrete and continuous domains. With the ever-increasing scale of data and the growing demand for effective distributed learning, a multitude of obstacles emerge, including communication limitations, resilience to failures and corrupted data, limited information access, and collaboration in multi-task learning scenarios. The thesis consists of seven chapters, each targeting specific aspects of these challenges.
In the first chapter, novel algorithms are introduced for collaborative linear bandits, offering a comprehensive exploration of the benefits of collaboration in the presence of adversaries through thorough analyses and lower bounds. The second chapter delves into multi-agent min-max learning problems by tackling the presence of Byzantine adversarial agents. Chapter three delves into the effects of delays within stochastic approximation schemes, investigating non-asymptotic convergence rates under Markovian noise.
Moving forward, the fourth chapter focuses on analyzing the performance of standard min-max optimization algorithms with delayed updates. The fifth chapter concentrates on robustness in discrete learning, specifically addressing convex-submodular problems in mixed continuous-discrete domains. The sixth chapter tackles the challenge of limited information access in collaborative problems with distributed constraints, developing optimal algorithms for submodular maximization under distributed partition matroid constraints.
Lastly, the seventh chapter introduces a discrete variant of multi-task learning and meta-learning. In summary, this thesis contributes to the field of robust collaborative learning and decision-making by providing insights, algorithms, and theoretical guarantees in discrete and continuous optimization. The advancements made across linear bandits, minimax optimization, distributed robust learning, delayed optimization, and submodular maximization pave the way for future developments in collaborative and multi-task learning.

CBE PhD Thesis Defense: "BIJEL-Templated Advanced Functional Materials for a Sustainable Future"
2023-07-14 12:00 - 13:30 | Towne 225
Advanced functional materials comprising multiple components with nano- and microscopic features typically rely on expensive and time-consuming fabrication methods. Kinetically-trapped disordered structures provide a powerful alternate route to fabricate fault-tolerant, multi-component functional structures at scale. Developing such structures with controllable features that could serve as materials templates for various applications is of great importance. Bicontinuous interfacially jammed emulsion gels (bijels) are kinetically trapped disordered biphasic materials that can be converted to porous materials with tunable features. The self-assembled nature of the bijel structure, coupled with its remarkable flexibility in terms of features and constituent materials, positions it as a highly promising material for the advancement of functional porous materials. However, the practical utilization of bijels is hindered by several challenges that need to be addressed. This study aims to overcome these challenges by simplifying the fabrication process, improving control over bijel features, and demonstrating their practical functions. To achieve scalable fabrication, the vaporization induced phase separation (VIPS) method is introduced, enabling bijel production under ambient conditions. The importance of quenching kinetics is also revealed, leading to the achievement of bijels with uniform sub-micrometer domains through regulated co-solvent removal. Furthermore, the unique structure of bijels allows for intriguing interactions with light, fluids, and electrons. This is exemplified by the successful development of bijel templated passive radiative cooling coatings and carbon air cathodes, showcasing the exceptional functionality of bijels.

PSOC@Penn Seminar: Gabriel Witek & Marco Aurelio Galvani Cunha
2023-07-17 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "Hydrogel (fracture) Mechanics with Applications to the Study of Blood Clots"
2023-07-18 10:00 - 11:30 | Moore 212
Blood clotting is primarily responsible for stemming bleeding in vessel injury, comprising a protective mechanism called hemostasis. However, if a blood clot forms within a blood vessel when or where it is not needed, this can result in death and disability. Blood clots and thrombi are composed of blood cells embedded into a polymeric fibrin network. The network is highly swollen with liquid (<1% solid volume fraction); biphasic porous media of such kind are called hydrogels. Both the solid and liquid phase, as well as their combined behavior, determine the properties of the hydrogel material. In this talk, we endeavor to understand the behavior of blood clots and thrombi, which are essential for hemostasis and thrombosis, by utilizing a continuum mechanics framework for hydrogels.
Loading of biological and synthetic hydrogels involves large deformations, and there exists a large literature devoted to their experimental characterization. Analytical investigations have recognized the importance of contributions originating from the liquid phase, while experiments have verified it. The liquid flux fields usually exhibit fully three-dimensional profiles and are time dependent. This coupled mechanical-diffusional poroelastic problem presents an abundance of interesting phenomena. One such interesting observation in many experiments is the tendency of the hydrogel material to expel liquid under tension. This behavior is well-documented in biological swollen tissues, but it appears to be absent from the vast majority of synthetic hydrogels. On the contrary synthetic gels swell during stretching, provided there is liquid to absorb from the surrounding environment. This motivates three types of boundary conditions in the coupled mechanical-diffusion problem for hydrogels: 1) gel immersed in a bath (permeable boundary conditions), 2) gel insulated from bath (impermeable), or 3) gel in an environment with a specific ambient moisture. In this talk all these boundary conditions and their implications will be discussed. The solid volume fraction, loading rate, type of loading, as well as geometry, influence the response of hydrogels dramatically. These factors are studied separately with some highlights from this study being presented. The energy release rate, a fundamental quantity of fracture mechanics, is computed using a poroelastic modified path (or surface)-independent J-integral. Liquid flow is shown to contribute an important amount to the energy release rate. Intriguingly, this contribution can be either positive or negative, the meaning of which will be discussed. To accommodate better understanding of the liquid contribution on the fracture energetics of these materials, a critical stretch criterion is adopted which is motivated from experimental evidence. Under critical conditions, the energy release rate is the fracture toughness of the material and its relation to the coupled response will be explained. These observations can be utilized to design toughening mechanisms for hydrogels based solely on the liquid phase of the material. The methods that will be presented can be utilized to analyze a wide variety of problems from mechano-chemical loading of biological and synthetic hydrogels to failure/damaging of batteries and large-scale soil mechanics.

PSOC@Penn Seminar: Sadjad Arzash & Ping Zhou
2023-07-24 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "Bistable Robots: Leveraging Task Features for Actuator Reduction"
2023-07-25 10:00 - 11:30 | Moore 212
Actuator reduction is especially important for aerial robots, where minimizing mass and conserving power is critical. Bistable mechanisms have been used to augment actuators by speeding up actuation time or allowing one direction of actuation to be passive. In this talk we will explore how bistable mechanisms can reduce the number of actuators needed in robotic applications. Traditional quadrotors exhibit agile flight, hovering, and landing. Inspired by birds and bats, recent developments aim to augment the capabilities of quadrotors with gliding or perching capabilities. However, current solutions require the addition of actuators. We demonstrate that bistable mechanisms can allow robots to exploit features in the task or environment to gain the desired functionality passively. Perching is an inherently contact-rich task, and incorporating a bistable structure enables us to exploit contacts for passive grasping and releasing. Flight is a highly dynamic task, and we demonstrate that bistable structures enable us to exploit inertia for passive wing deployment. Thus, bistability enables us to endow aerial robots with additional capabilities without adding additional motors.

Penn American Red Cross Blood Drive
2023-07-28 11:00 - 16:00 | Bodek Lounge, Houston Hall, 3417 Spruce St, Philadelphia, PA, 19104, United States
There is currently a critical need for blood donors, and members of the Penn Engineering community are invited to participate in a school-wide blood drive. To join in this effort, please RSVP using this link.

PSOC@Penn Seminar: Yiming Wang & Ison Chen
2023-07-31 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "Mechanics- Informed Optimization for Enhanced Adhesion and Toughness"
2023-08-01 10:00 - 11:30 | Towne 337
Structural design optimization has long played a crucial role in engineering, often with the goal of creating stiff and lightweight structures for aerospace and other applications. However, optimizing structures against failure is also crucial and has been much less well explored. Failure via fracture and at interfaces is particularly challenging in design optimization as they involve high local stress concentrations and singular stresses. In this talk, we demonstrate how mechanics models can be integrated with optimization schemes to engineer structures with improved interface adhesion and fracture toughness. Specifically, four distinct structural design cases are considered: adhesive fibrils, shear lap joints, architected adhesive joints, and adaptive mechanical networks. The computational framework couples finite element analysis with multiple optimization methods, including gradient and heuristic-based techniques, as well as machine learning-based approaches. We show that performance can be improved by formulating optimization schemes and objective functions based on the principles of mechanics and failure. Optimal designs are determined via the computational schemes and validated via experiments on several different material systems. The versatility of the computational and optimization schemes that have been developed enables them to be extended to other scenarios where performance can be improved by optimizing geometry to control stresses.

ESE PhD Thesis Defense: "Software/Hardware Co-optimization for Computer Systems with 3D-stacking Memories"
2023-08-03 15:00 - 17:00 | Moore 317, 200 S 33rd Street, Philadelphia, PA, 19104, United States
Emerging 3D memory technologies, such as the Hybrid Memory Cube (HMC) and High Bandwidth Memory (HBM), provide high bandwidth and massive memory-level parallelism. With the growing heterogeneity and complexity of computer systems (CPU cores and accelerators, etc.), efficiently integrating emerging memories into existing systems poses new challenges to both algorithm, hardware and system. This dissertation explores the application-aware system optimization techniques for 3D-stacking memory in both domain-specific accelerators (DSAs) and general-purpose computer systems. The first part of the dissertation presents a standalone 3D-Stacking memory-based graph accelerator that can achieve 45.8 billion traversed edges per second (TEPS) by co-optimizing the algorithm and the hardware architecture. We first present the modifications of algorithm and a platform-aware graph processing architecture to perform level-synchronized breadth first search (BFS) on FPGA-HMC platform. To gain better insights into the potential bottlenecks of proposed implementation, we develop an analytical performance model to quantitatively evaluate the HMC access latency and corresponding BFS performance. Based on the analysis, we propose a two-level bitmap scheme to reduce memory access and perform optimization on key design parameters (e.g. memory access granularity). Then, we leverage the inherent graph property i.e. vertex degree to co-optimize algorithm and hardware architecture. In particular, we first develop two algorithm optimization techniques: degree-aware adjacency list reordering and degree-aware vertex index sorting and two platform-dependent hardware optimization techniques, namely degree-aware data placement and degree-aware adjacency list compression. These two techniques together substantially reduce the amount of access to external memory. Finally, we conduct extensive experiments on an FPGA-HMC platform to verify the effectiveness of the proposed techniques. In the second part of this dissertation, we develop machine learning methods that can automatically identify access patterns of major variables in a program. These methods can then cluster these variables with similar access patterns to reduce the overhead for SDAM. Our evaluation on standard CPU benchmarks and data-intensive benchmarks (for both CPU and accelerators) demonstrates a 1.41x and1.84x speedup on CPU and a 2.58x speedup on near-memory accelerators in our system with SDAM, compared to a baseline system.

PSOC@Penn Seminar: Geng-Yuan "Scott" Chen & Alisya Anlas
2023-08-07 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "Wall-modeled Large-eddy Simulation of Non-Equilibrium Turbulent Boundary Layers"
2023-08-08 10:00 - 11:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Accurate prediction of high-Reynolds-number turbulent flows is essential for the understanding and flow control of many engineering applications such as aircraft, turbomachinery, and marine vehicles. Additionally, most practical flows exhibit nonequilibrium effects such as pressure gradients and flow separation. However, the direct numerical simulation (DNS) of high-Reynolds-number wall-bounded turbulent flows is not feasible owing to the prohibitive computational cost of resolving small-scale eddies near the wall. Wall-modeled large-eddy simulation (WMLES) presents an affordable predictive alternative to the DNS via approximate modeling of flow physics near the wall (through a wall model) while resolving the outer (larger) scales directly on the computational grid. In this talk, we will explore three wall models with varying degrees of computational complexity and physical fidelity, to assess their performance in two controlled nonequilibrium flows over a flat plate. The first flow features a turbulent boundary layer undergoing a series of complex pressure gradient effects, while the second exhibits turbulent flow separation induced by suction and blowing. While in the latter case, the more complex model clearly produces a superior prediction of the wall shear stress, the same is not necessarily true in the former case, highlighting the importance of adapting the wall models to different flow physics. We will show how differing mechanisms within wall models lead to the observed results.

BE Doctoral Dissertation Defense: "Microfluidics for throughput scalable formulation of mRNA lipid nanoparticle technology" (Sarah Shepherd)
2023-08-10 15:00 - 17:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania along with Drs. Dave Issadore and Mike Mitchell proudly announce the Doctoral Dissertation Defense of Sarah Shepherd.

Title: Microfluidics for throughput scalable formulation of mRNA lipid nanoparticle technology

Date: August 10, 2023
Time: 3:00 PM
Location: Wu & Chen Auditorium, Levine Hall

Zoom option:
https://us04web.zoom.us/j/78754123595?pwd=[REDACTED]
Meeting ID: 787 5412 3595
Passcode: [REDACTED]

The public is welcome to attend.

Summer 2023 GRASP Seminar: Claire Tomlin, University of California at Berkeley, “Safe Learning in Control”
2023-08-11 14:00 - 15:00 | GRASP Treehouse – Pennovation Complex; LAB Building (Bldg 250 – Suite 250), 3401 Grays Ferry, Philadelphia, 19146, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom.

ABSTRACT
In many applications of autonomy in robotics, guarantees that constraints are satisfied throughout the learning process are paramount. We present a controller synthesis technique based on the computation of reachable sets, using optimal control and game theory. Then, we present methods for combining reachability with learning-based methods, to enable performance improvement while maintaining safety, and to move towards safe robot control with learned models of the dynamics and the environment. We will discuss different interaction models with other agents, and some implications of model vs. learning-based predictions.

MEAM Seminar: "Hierarchical Methods for Geometric Control of Underactuated, Free-Flying Robotic Systems"
2023-08-15 10:00 - 11:30 | Towne 337
Free-flying robotic systems (such as multibody aerial and space vehicles) evolve on high-dimensional non-Euclidean manifolds subject to nonlinear, underactuated dynamics. Because such systems can rely only on the severely limited computational resources available onboard, the design of general-purpose controllers capable of dynamic and reliable real-time performance remains a formidable challenge. To mitigate these obstacles and achieve the stated goals across a broad class of systems, we seek geometric insight into structural properties that transcend individual robot morphologies, developing systematic methods of controller synthesis by leveraging these features. First, we exploit the Noetherian symmetry and Riemannian structure inherent to their dynamics, revealing a class of systems that admits a certain hierarchical decomposition. In such a representation, the motion of the system’s internal degrees of freedom is completely determined by the bulk motion through its symmetry group (e.g. its position and orientation). Examples of such systems include aerial manipulators consisting of an underactuated vehicle equipped with a robotic arm. Second, in order to design and certify hierarchical controllers that leverage this structure, we prove new basic results on the stability of cascades whose subsystems are only almost globally asymptotically stable, the best possible property for smooth vector fields on general manifolds. Lastly, in our ongoing work we apply these theoretical insights to inform mechanical design and controller implementation in pursuit of a small and agile aerial manipulator capable of precise, dynamic operation.

MEAM Ph.D. Thesis Defense: "Exploiting Flows for Orienteering and Planning Problems"
2023-08-16 14:00 - 15:00 | Towne 337
Task and path planning algorithms for robots in the presence of flows confront a fundamental dichotomy between the continuous and the discrete: task planning algorithms discretize the world and their goals, whereas flows are continuous in nature. This contrast is exemplified in many robotic applications where environmental forces impact navigation and exploiting those flows is critical for the quality of results. In this work, we address methods for connecting continuous models of the environment with planning methods for robot motion in high-level task planning with low-level path planning.
First, we examine a problem that focuses on the high level problem of task planning, but abstracts away the environment and assumes that the low-level path planning is solved independently. This helps simplify the problem, but neglects to include environmental information which is often fundamentally linked to the vehicle motion. Next, we address this limitation by exploring path planning algorithms in environments that are represented by an external flow field, such as static and time-varying ocean currents. While we cannot control the external currents, our planning method considers the trade-offs between energy efficiency, reward collection, and time budget based on the interplay of the chosen routes, paths, and environment. Lastly, we expand our analysis to the joint problem of both designing the environmental flows and path planning within the designed flow fields. We explore this problem in the context of controlling magnetically driven milli-robots. We show how we can circumvent the need to solve the inverse dynamics problem with complete knowledge of the global field by extracting key features from the generated fields. These features enable us to take a topological approach to discretize the search space and design advantageous paths.

NCI Junior Investigator Meeting
2023-08-17 17:15 - 2023-08-18 18:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
University of Pennsylvania will be hosting the NCI Junior Investigator Meeting this year. The meeting includes several talks throughout the day and poster sessions (5:15 pm Thursday & 4:00pm Friday)

NCI Junior Investigator Meeting
August 17-18, 2023
Wu & Chen Auditorium, Levine Hall

University of Pennsylvania
Philadelphia, PA

Please see the website for details: https://events.cancer.gov/dcb/ji-meeting

Nano Seminar: "Conductive Nitrides for Plasmonics in the Visible Region: Properties and Applications"
2023-08-18 11:00 - 12:00 | Room 35, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Plasmonic nanostructure based on silver and gold that produces LSPR to withstand ultrahigh temperatures without damage remains a great challenge for future ultra-compact integrated circuits, and high-power enabled photonic devices. In principle, the shapes of plasmonic nanostructures containing noble metals would change after the heat treatment that altered the plasmonic resonance. Thus, discovering refractory plasmonic materials that can exhibit plasmonic resonance in the visible range is essential. A challenge in refractory plasmonic materials is the bulk plasmon frequency is usually in the near-infrared range, making it difficult to generate plasmonic colors in the visible. We first reported a new refractory plasmonic material HfN, one of the conductive nitrides, that has a relatively high bulk plasmon frequency (λ = 400 nm) with a high melting point (T ∼ 3583 K) and a relatively large magnitude of the real part of the permittivity, which enables intense local electromagnetic field confinement to form LSPR in the visible region. We use this unique property to develop full-color plasmonic pixels with sub-diffraction resolution through tailoring HfN plasmonic crystals and demonstrate that HfN refractory plasmonic crystals can withstand high-temperature annealing (900 °C) without damage. The novel HfN refractory plasmonic materials unlock new opportunities for ultra-compact integrated functional plasmonic devices. Especially the unique property of HfN, implying a bright future for emerging plasmonic materials at visible wavelengths [1]. In addition, I will present an overview of my research works over the past five years on the plasmon-enhanced light-matter interactions in the visible regions and their applications [1-6], including the plasmonic nanolasers [2-3], tunable plasmonic modulators [4], plasmonic phototransistors [5], plasmon-enhanced solar energy harvesting [6], and the refractory plasmonic colors for back-light free displays [1]. My group discovered several unique working mechanisms that utilize plasmonic nanocavities to improve optoelectronic device performance. More recently, we demonstrated the scalable 2D FET device fabrication and characterization [7]. By engineering the local electromagnetic field confinement, the light-matter interaction strength can be enhanced, which results in efficient energy conversion in the designed nanosystem. Lastly, I will discuss detailed mechanisms and possible applications. These results have broad implications for the use of alternative plasmonic nanocavities in high-performance optoelectronic devices.

MEAM Ph.D. Thesis Defense: "Mobile Wireless Infrastructure on Demand in Robot Teams"
2023-08-21 10:00 - 11:00 | 216 Moore Building
Communication is fundamental to successful coordination in teams of robots. Indeed, the promise that robot teams can complete tasks faster and more efficiently than any single agent depends on their ability to share information and effectively coordinate their actions. Today, teams of mobile robots are increasingly being deployed to tackle challenging tasks in environments without existing network infrastructure, relying instead on peer-to-peer communication. While there exists a considerable body of research dedicated to maintaining network connectivity, we still lack methods that are efficient, scalable, and practical. In this thesis we take a number of steps to address these challenges. First, we formalize the problem of Mobile Infrastructure on Demand (MID), wherein a team of mobile robots are deployed to create and sustain a wireless network that supports the communication requirements of a different set of task-oriented robots collaborating to accomplish an objective. This approach decouples the task planning and network maintenance problems and allows us to focus on developing algorithms for the communication/MID team that are task agnostic, enabling a large class of multi-robot algorithms to function without existing network infrastructure. Second, we demonstrate a data driven approach to the MID agent placement problem using convolutional neural networks (CNNs) that achieves comparable performance to an optimization based expert in a fraction of the time and scales to large teams. Finally, we introduce a complete solution to the MID problem that optimizes the position of mobile network relay nodes to directly improve the performance of the underlying routing protocol. We demonstrate our system in a set of experiments with ground robots equipped with 802.11 WiFi radios performing situational awareness and multi-robot exploration.
