Penn Engineering Events

MEAM Seminar: "Toward Agile Legged Locomotion in a Novel Quadrupedal Robot with an Axially Twisting Spine"
2022-08-16 10:00 - 11:30 (America/New_York) | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
With the advent of more capable and cheaper legged robots, robotic legged locomotion is becoming an increasingly attractive solution for locomotion and embodiment. Legs offer expanded capability over wheeled robots, albeit at the cost of complexity and efficiency. For example, walking robots explore rubble-filled caves, inspect industrial sites, move around human spaces (e.g., stairs), and travel in natural environments. Still, the current capabilities of most robots pale in comparison to most biological-legged locomotors. For instance, the arboreal squirrel can run from branch to branch, climb up and down trees, and leap from surface to surface, composing strings of maneuvers without slowing or stopping. Taking biology as inspiration, collaborations with mathematicians, biomechanists, paleontologists, and geologists help us distill down the essential locomotor primitives and morphologies for new, more agile, quadrupedal robots.
My research focuses on the benefits of adding novel internal degrees of freedom to quadrupeds (namely an axially twisting spine), especially in spatial, transitional maneuvers. In this talk, I will show some results and preliminary work using physical models and optimization to suggest that investigating spinal degrees of freedom is vital in opening up the capabilities of legged quadrupeds. Next, I will introduce a novel quadrupedal robot, Twist, walk through its design process, describe the context of its design, and elaborate on some questions we hope to solve within and outside the field of robotics. Finally, I will discuss my work toward these transitional (parkour) behaviors in robotics, particularly regarding moving from a sagittal plane model and robot to an intrinsically spatial, three-dimensional model and robot.

Quantum Engineering Summer Seminar Series: Peter McMahon, PhD [quantum annealing] (Cornell University)
2022-08-12 12:00 - 13:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
About the Series: The Quantum Engineering Summer Seminar Series is hosted by the Quantum Engineering Graduate Association (QEGA) every Friday at 12:00 – 1:00 pm EDT throughout the summer months and will be followed by a separate Fall series. The series invites leading world leading experts across academia, industry, and government working on experimental, theoretical, and policy aspects of quantum science and engineering. Each seminar will be followed by a 10 minute networking session with the invited speaker.
Speaker List:
July 8th, 2022 – Jon Felbinger, PhD [private-public partnerships] (Quantum Economic Development Consortium)
July 15th, 2022 – William Oliver, PhD [superconducting qubits] (MIT and MIT Lincoln Labs)
July 22nd, 2022 – Sinead Griffin, PhD [novel qubit materials design] (Lawrence Berkeley National Laboratory)
July 29th, 2022 – Hannes Bernien, PhD [trapped ion systems] (University of Chicago)
August 5th, 2022 – Prineha Narang, PhD [computational quantum dynamics] (Harvard University)
August 12th, 2022 – Peter McMahon, PhD [quantum annealing] (Cornell University)
August 19th, 2022 – Nick Bronn, PhD [NISQ era quantum computing] (IBM)
August 26th, 2022 – Riccardo Manenti, PhD [scalable quantum computing systems] (Rigetti)
Meeting Information: The seminar series will be a hybrid event with talks broadcasted on campus (Wu and Chen Auditorium, Levine Hall) and available online via Zoom. The Zoom link will be posted weekly for each individual talk.
Join QEGA: The Quantum Engineering Graduate Association (QEGA) is a new organization at Penn founded by Nima Leclerc and Noah Johnson, two Penn ESE PhD students in the Sigillito Group. QEGA’s goal is to increase graduate student and faculty engagement in quantum engineering at Penn through school-wide events such as this seminar series, quantum-career networking opportunities, and a quantum engineering outreach program program. If you would like to stay connected with us, please email Nima at nleclerc@seas.upenn.edu with the subject line ‘qega listserv’ to get added to our mailing list!

MEAM Seminar: "Data-Driven Model Discovery for Non-equilbrium Processes via Stochastic Thermomechanics"
2022-08-09 10:00 - 11:30 | Towne 313, 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.
In this talk, I will leverage several different recent advances in non-equilibrium physics, together with emerging machine learning techniques, to develop data-driven computational strategies for learning continuum evolution equations. First, I will present a new strategy for continuum model discovery to systems that have both a reversible (elastic) and dissipative evolution, by using fluctuation theorems, particularly, the Jarzynski equality. Second, I will talk about a proposed machine learning architecture called Variational Onsager Neural Networks (VONNs) to learn the non-equilibrium evolution PDEs based on the Onsager’s variational approach. Finally, I will introduce a statistical mechanics framework with quantified uncertainty to extrapolate material behavior to different loading conditions (including far-from-equilibrium conditions) or material systems.

Quantum Engineering Summer Seminar Series: Prineha Narang, PhD [computational quantum dynamics] (Harvard University)
2022-08-05 12:00 - 13:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "Neural Network Assisted Open Boundaries for Molecular Dynamics Simulations"
2022-08-02 10:00 - 11:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Molecular dynamics simulations allow for the visualization and analysis of atoms and molecules. The choice of boundary conditions in these simulations can impact the overall system, and is an important design decision. In particular, open boundary molecular dynamics simulations is one type of methodology that allows for the treatment of atomistic models with non equilibrium conditions. In this seminar, I introduce an approach to the treatment of open boundaries using machine learning. A neural network-assisted design will be presented that can emulate the physics and reduce the computational cost of open boundary simulations. Particle influxes and neural network-derived forces are applied at the boundaries of an open domain consisting of explicitly modeled Lennard-Jones atoms in order to represent the effects of an unmodeled surrounding fluid. Canonical ensemble simulations with periodic boundaries are used to train the neural network and to sample boundary fluxes. The method, as implemented in the LAMMPS molecular simulation package, yields results comparable to those calculated using periodic molecular dynamics and runs two orders of magnitude faster than a comparable grand canonical molecular dynamics system.

MEAM Ph.D. Thesis Defense: "Imperfect Adhesion Between Elastic Solids"
2022-08-01 10:30 - 12:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Surface force-mediated adhesion, i.e. via van der Waals forces, is critical for the direct bonding of bulk solids in the absence of an adhesive layer. However, no two surfaces are perfectly flat nor conformal and some have intentional patterns, which leads to imperfect adhesion, i.e. interface adhesion strength that is below its ideal strength. In the case of non-conformal patterned interface, regions of tensile and compressive stresses exist in the adhered solids at the equilibrium state. Imperfect adhesion also can arise from edge effects. The understanding of imperfect adhesion is important in controlling interfacial strength and toughness for various applications including MEMS/NEMS, micro-transfer printing, and soft robotic grippers.
The overall goal of this thesis is to investigate the mechanics of surface force-mediated adhesion by examining the interplay between intrinsic traction-separation relation (TSR), interface topography, and elastic bulk properties. The TSR developed accounts for strong repulsion to avoid material interpenetration. The effective interface properties, including the overall adhesion strength and work of separation, are determined from numerical calculations using finite element analysis.
The first study exploits surface patterning for adhesion control. A cohesive model for a periodic unit cell with non-conformal patterned interfaces is developed to analyze the joint effects of non-uniform interface separation and elastic bulk deformation. The second study investigates edge effects. In general, interface shear tractions coupled with Poisson contraction reduces the interface adhesion significantly and result in fracture-based failure. Understanding the interaction between the normal and the shear tractions is important but has not been studied extensively thus far. The second study concerns the detachment of an elastic pillar from a rigid substrate. A non-dimensional parameter is defined to describe the transition between strength-based and fracture-based failure. In a third study, the mechanics that govern interface failure in electroadhesives is investigated using a TSR derived from Coulomb’s law. This last study highlights the importance of interface crack growth in the design of electroadhesives through modeling an elastic cylinder electrostatically adhered to a rigid substrate. The adhesion strength of the electroadhesives becomes imperfect when a non-dimensional parameter reaches a critical value.

BE Doctoral Dissertation Defense: "Designing Hyaluronic Acid Granular Hydrogels for Biomaterials Applications" (Victoria Grace Muir)
2022-07-29 12:00 - 14:00 | Class of 62 Auditorium, John Morgan Building, 3620 Hamilton Walk, Philadelphia, PA, 19104
The Department of Bioengineering at the University of Pennsylvania and Dr. Jason Burdick are pleased to announce the Doctoral Dissertation Defense of Victoria Grace Muir.

Title: Designing Hyaluronic Acid Granular Hydrogels for Biomaterials Applications
Date: Friday, July 29th, 2022
Time: 12pm ET
Location: John Morgan Building, Class of 62 Auditorium, 3620 Hamilton Walk, Philadelphia, PA 19104.

The public is welcome to attend.

Quantum Engineering Summer Seminar Series: Hannes Bernien, PhD [trapped ion systems] (University of Chicago)
2022-07-29 12:00 - 13:00 | https://upenn.zoom.us/j/96715197752

BE Doctoral Dissertation: "Fundamentals and Application of 3D Suspension Bath Bioprinting for the Engineering of Meniscal Tissue" (Margaret Prendergast)
2022-07-29 09:00 - 11:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Jason Burdick are pleased to announce the Doctoral Dissertation Defense of Margaret Prendergast.

Title: Fundamentals and Application of 3D Suspension Bath Bioprinting for the Engineering of Meniscal Tissue
Date: Friday, July 29th, 2022
Time: 9 AM ET
Location: Towne Building, Room 337, 107 Towne Bldg, Philadelphia PA 19104
(If you wish to join virtually, Please reach out to Maggie (prendm@seas.upenn.edu) for zoom link and passcode.)

MEAM Seminar: "Motion Planning for a Variable Topology Truss Robot"
2022-07-26 10:00 - 11:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Variable Topology Trusses (VTTs) are a new type of modular, self-reconfigurable robot (MSRR). Like other self-reconfigurable robot systems, a VTT can change its shape to adapt to a variety of tasks, offering a wider range of capabilities than a single robot configuration. While most MSRRs consist of robot modules that are connected in a chain or lattice architecture, VTTs use a truss-based architecture instead. A VTT can be thought of as a variable geometry truss—a set of linear actuator modules that are connected together to form a rigid structure—with the additional ability to reconfigure by merging and splitting the truss nodes. This truss architecture gives improved structural efficiency and scalability, but it presents unique challenges for motion planning and reconfiguration planning.
In this talk, I will first introduce the Variable Topology Truss concept and show our recent progress on developing the robot hardware. Then, I will present my work on motion planning for reconfiguration and shape morphing of VTTs. Traditional probabilistic motion planning techniques are ineffective because the collision constraints generate a configuration space with many narrow passageways and inaccessible regions. I will present a technique that guides a motion planner by leveraging the topological and knot-theoretic information embedded in a robot configuration.

MEAM Ph.D. Thesis Defense: "The Design of a Community-Informed Socially Interactive Humanoid Robot and End-effectors for Novel Edge-Rolling"
2022-07-25 15:00 - 16:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
This dissertation discusses my work in building an HRI platform called Quori and my once separate now integrated work on a manipulation method that can enable robots like Quori, or any more capable robot, to move large circular cylindrical objects.
Quori is a novel, affordable, socially interactive humanoid robot platform for facilitating noncontact human-robot interaction (HRI) research. The design of the system is motivated by feedback sampled from the HRI research community. The overall design maintains a balance of affordability and functionality. Ten Quori platforms have been awarded to a diverse group of researchers from across the United States to facilitate HRI research to build a community database from a common platform.
This dissertation concludes with a demonstration of Quori transporting a large cylinder for which Quori does not have the power to lift nor the range of motion to dexterously manipulate. Quori is able to achieve this otherwise insurmountable tasks through a novel robotic manipulation technique called robotic edge-rolling. Edge-rolling refers to transporting a cylindrical object by rolling on its circular edge, as human workers maneuver a gas cylinder on the ground for example. This robotic edge-rolling is achieved by controlling the object to roll on the bottom edge in contact with the ground, and to slide on the surface of the robot’s end-effector. It can thus be regarded as a form of robotic dexterous, in-hand manipulation with nonprehensile grasps. This work mainly addresses the problem of grasp planning for edge-rolling by studying how to design appropriately shaped end-effectors with zero internal mobility and how to find feasible grasps for stably rolling the object with the simple end-effectors.

Physical Sciences Onco-development Colloquium (PSOC): "From physics to therapeutics – An entrepreneurial journey across disciplines" (Kandaswamy Vijayan)
2022-07-25 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Physical Sciences Onco-development Colloquium (PSOC)
Hybrid talk in Raisler Lounge and on Zoom (contact manu@seas.upenn.edu for the Zoom link).

Quantum Engineering Summer Seminar Series: Sinead Griffin, PhD [novel qubit materials design] (Lawrence Berkeley National Laboratory)
2022-07-22 12:00 - 13:00 | https://upenn.zoom.us/j/96715197752

BE Doctoral Dissertation: "Rapid, scalable, amplified RNA detection in situ with clampFISH 2.0" (Ian Dardani)
2022-07-21 13:00 - 15:00 | Smilow Center for Translational Research, Room 09-146
The Department of Bioengineering at the University of Pennsylvania and Dr. Arjun Raj are pleased to announce the Doctoral Dissertation Defense of Ian Dardani.

Title: “Rapid, scalable, amplified RNA detection in situ with clampFISH 2.0″

Date: Thursday, July 21, 2022
Time: 1pm ET

Add to Google Calendar
Location: In-person: Smilow Center for Translational Research, Room 09-146
Zoom: https://upenn.zoom.us/j/94182106925

MEAM Seminar: "Modboats: Building an Aquatic Modular Self-Reconfigurable Robotic System out of Underactuated Modules"
2022-07-19 10:00 - 11:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Modular robots offer the promise of flexibility; we will be able to deploy teams of generalist modules and reconfigure them into various specialists to perform whatever task is necessary. Surface swimming aquatic modular robots in particular are not well studied, however, because the literature assumes that the modules need to be holonomic, which makes them expensive and difficult to build and maintain. We disrupt this assumption with the Modboat – an inexpensive, underactuated surface swimmer that uses only one motor to propel and steer itself along the ocean surface, and is capable of all the behaviors required of a modular self-reconfigurable robotic system (MSRR). In this seminar, I present my work on designing the Modboat modules, achieving near holonomic motion capabilities using temporal multiplexing, and developing the capabilities needed for modular self-reconfiguration.

PSOC@Penn Talk: David Basanta Gutierrez & Conor C. Lynch (Moffit Cancer Center)
2022-07-18 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Contact manu@seas.upenn.edu for the Zoom link.

Quantum Engineering Summer Seminar Series: William Oliver, PhD [superconducting qubits] (MIT and MIT Lincoln Labs)
2022-07-15 12:00 - 13:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

ESE Ph.D. Thesis Defense: "Creating dynamical robots of different morphologies and sizes through automatic origami design"
2022-07-14 12:30 - 14:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Origami robots are machines whose morphologies and functions are created by folding locally flat sheets. This thesis makes three contributions to the design and fabrication of origami robots aimed at the development of an automated computational pipeline for the specification and construction of widely different morphologies and body sizes capable of highly dynamic operation. The initial contribution recruits recent advances in the design of compliant folded structures to build the first soft robots that exhibit highly dynamic behavior. Specifically, the proof-of-concept robots reported here achieve their juggling and hopping behaviors by actuating their origami springs as power-cascading devices. Second, this thesis advances the origami design literature by automating the construction of compliant origami kinematic chains. The “Kinegami” algorithm reported here accepts a Denavit-Hartenberg kinematic specification and uses a catalog of tunably compliant origami modules to generate a crease pattern that folds into the prescribed serial robot mechanism. Finally, the thesis addresses the problem of scalability in general (not just origami) robot design by studying the simultaneous interaction of structural integrity and actuator affordance. Four contrasting abstract task domains impose different scaling criteria that reveal the relative advantages and disadvantages of three distinct structural principles combined with three different actuator types. For example, applying the unloaded dynamic task criterion to a direct drive actuation type reveals that the origami-style shell structure supports superior length scale-up. An accompanying empirical study confirms that structural alternatives cannot achieve a one-degree-of-freedom hopping task at the same five-fold scale-up of the original hopper design exhibited by the shell structure design.
Considered in isolation, these contributions advance, respectively, the recent soft robotics literature, the older origami design literature, and the traditional engineering scaling literature. Considered together, they advance the agenda for the rapid, computer-assisted design of customized, high-performance robots.

ESE Ph.D. Thesis Defense: "Learning Environmental Models with Multi-Robot Teams Using a Dynamical Systems Approach"
2022-07-14 10:00 - 12:00 | PERCH 303, Pennovation 3rd Floor, 3401 Grays Ferry Avenue, Bldg 6176, Philadelphia, PA, 19146, United States
Robots have the capability to sense and track natural phenomena for environmental monitoring, deepening our understanding of the world. Robotic modeling of such phenomena is essential to operating in complex environments, allowing robots to perform in more realistic scenarios. Thus, representing complex environments is paramount to the success of multi-robot teams. While considerable efforts have been made for modeling with multi-robot teams, specifically in coordination and distributed methods, these techniques have limitations in spatiotemporal, complex environments. These environments can be vastly different, such as fluid flows, oceans, and space. Robots operating in these environments typically create representations of their surroundings using computationally expensive techniques or by leveraging human expert knowledge.
Interestingly, though these environmental processes may seem unrelated, they can all be analyzed with dynamical systems theory. This thesis presents methods for representing the environment as a dynamical system with machine learning techniques. We formulate machine learning methods that lend to data-driven modeling of the phenomena for robotic applications, specifically using dimensionality reduction techniques and kernel methods. The data-driven modeling explicitly leverages theoretical foundations of dynamical systems theory. Dynamical systems theory offers mathematical and physically interpretable intuitions about the environmental representation. The procedures presented include distributed algorithms, online adaptation, uncertainty quantification, and feature extraction to allow for the actualization of these techniques on-board robots. The environmental representations guide robot behavior in developing strategies such as optimal sensing and energy-efficient navigation. The methods and procedures provided in this thesis were verified across prototypical environments and on experimental robots.

ESE Ph.D. Thesis Defense: "Optical and Spin Dynamics of Quantum Emitters in Hexagonal Boron Nitride at Room Temperature"
2022-07-13 10:00 - 11:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Hexagonal boron nitride (h-BN) is a van der Waals material that hosts defect-based quantum emitters (QEs) at room temperature, providing an unparalleled platform for realizing devices for quantum technologies and studying light-matter interactions. Recent observations suggest the existence of multiple distinct defect structures responsible for QEs. Theoretical proposals suggest vacancies, substitutional atoms, and their complexes as likely defect candidates. However, experimental identification of the QEs’ electronic structure is lacking, and key details of the QEs’ charge and spin properties remain unknown. This thesis focuses on understanding the optical and spin dynamics of QEs in h-BN at room temperature. Starting with the motivation for studying quantum systems and QEs, this thesis introduces QEs in h-BN and discusses its current understanding. Next, it discusses the materials and methods developed and utilized during the course of this thesis. Next, it discusses the optical dynamics acquired using photoluminescence spectroscopy and photon emission correlation spectroscopy (PECS) and shows several QEs exhibit pure single-photon emission. It discusses the complex optical dynamics associated with excitation and relaxation through multiple electronic excited states – revealed by PECS and polarization-resolved excitation and emission. Following, it presents the optical dynamics simulations of electronic structure models that are consistent with the observations, and discusses the results in the context of ab initio theoretical calculations. Next, it discusses magnetic-field-dependent PECS that can be used as a framework to probe the presence of single spins that are otherwise elusive. Following, it presents detection and confirmation of single-spin using optically detected magnetic resonance. Finally, it discusses the spin dynamics and time-domain measurements acquired using optical and microwave pulse protocols crucial to developing methods to coherently control the QE’s spin. To conclude, it discusses the future directions that can help identify the chemical nature of QEs in h-BN and establish it as a scalable material platform for quantum technologies.

MEAM Seminar: "Sedimentation of Active Suspensions: Hindrance and Phase-separation"
2022-07-12 10:00 - 11:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Sedimentation of active matter is found in many natural and industrial processes. It plays an important role on the distribution of plankton in oceans, which is key part of the carbon cycle (i.e. ocean’s biological pump) that transports carbon from the ocean’s surface to depth. In this seminar, I will present an investigation on the dynamics of the sedimentation of spherical colloids in presence of swimming microorganisms at various concentration within the dilute regime. In the first part of this talk, I will show how bacterial activity hinders the sedimentation speeds of passive particle. These results can be described by an advection-diffusion equation with an added population dynamics term. In the second part of this talk, I will show the appearance of two sedimentation fronts, particle and bacterial. Even passive systems of poly-dispersed (by size) particles are known to show segregating sedimentation fronts; larger (and faster) settling particles will separate from smaller (and slower) ones, given enough time. Here, I will show how the increase of activity affects sedimentation speeds and the timescales associated with the appearance of the bacteria front. These timescales associated with the second front leads to a phenomenological model that captures the sedimentation of passive particles in active fluids.

PSOC@Penn: “Fat accumulation induces heterogeneous regions of softness in fatty liver” (David Li)
2022-07-11 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

Quantum Engineering Summer Seminar Series: Jon Felbinger, PhD [private-public partnerships] (Quantum Economic Development Consortium)
2022-07-08 12:00 - 13:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "Mixing with Activity: Transport of Swimming Microorganisms in Complex Flows"
2022-07-05 10:00 - 23:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
How will swimming microorganisms affect the mixing of a diffusive contaminant in chaotic flows? Answers to this question can lead to improved understanding of the spread of pollutants (e.g. algal blooms) in oceans and lakes, as well as potentially useful applications in biofuel and vaccine productions. In this talk, I present recent experiments on the chaotic mixing of a passive pollutant in dilute suspensions of swimming Escherichia coli. I will first discuss the results in a two-dimensional (2D) time-periodic flow that preserves spatial symmetry. Second, I will extend these results to a more realistic case of spatially disordered 2D vortical flows that resemble geological flows in nature. Overall, these results show that the interaction between active swimming particles and dynamical structures of the flow (i.e. Lagrangian coherent structures) can lead to profound changes in the transport and mixing of passive scalar quantities.

MEAM Ph.D. Thesis Defense: "Enhancing Strength and Toughness Via Reinforcement with Nanocellulose Fibers"
2022-06-28 10:00 - 11:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Cellulose nanofibrils (CNFs) are a nanomaterial obtained from plant sources and have excellent mechanical properties, high aspect ratios, and are biodegradable. As a reinforcing phase, CNFs have the potential to improve the mechanical properties of polymer materials. The overarching objective of this thesis is to investigate the use of CNFs to enhance the strength and toughness of polymers and traditional papers.
In the first part of this thesis, poly methyl methacrylate (PMMA) fibers are reinforced using CNFs to increase the strength and toughness. Fourier transform infrared (FTIR) spectroscopy is used to measure PMMA molecular orientation in the composite fibers. Tensile tests and fiber-based fracture tests using edge-cracked fibers are used to quantify the enhancement of modulus, strength, and fracture toughness through the addition of CNFs to PMMA. Specifically, a 2 improvement in fracture toughness is observed at 1% wt. CNF content.
In the second part of the thesis, filter paper, which is a network of microscale cellulose fibers is infiltrated with CNFs to create all-cellulose sheets with heterogenous mechanical properties. This is realized by printing and subsequent drying of an aqueous CNF solution and patterning of the infiltrated regions is used to engineer the strength and toughness of the materials. Single edge notch tension (SENT) tests are performed on the specimens to evaluate their fracture behavior. It is shown that geometric and elastic heterogeneity can be utilized to tune the toughness over a large range while maintaining or improving the strength.
Finally, to overcome limitations of the SENT, a new experimental fracture specimen, denoted the hinged rigid beam (HRB), was developed. The HRB eliminates the compressive stresses developed in conventional beam-bending fracture tests like the double cantilever beam method, thus making it suitable for testing thin materials such as paper. A mechanics model of the HRB was developed to allow critical strain energy release rate to be calculated from the measured force-displacement response and the specimen was validated via finite element analysis and experiments on thin PMMA sheets. This technique was used to characterize the toughness of several materials, including filter paper, copy paper and 2D lattice materials. Finally, the HRB was used to characterize and further understand the fracture behavior of patterned nanocellulose infiltrated sheets.

PSOC@Penn Talk: "Microtechnology-based Single Cell and EV Profiling” (Jina Ko)
2022-06-27 12:00 - 13:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

ESE Ph.D. Thesis Defense: "Machine Learning on Large-Scale Graphs"
2022-06-27 10:00 - 12:00 | Room 452 C, 3401 Walnut, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Graph neural networks (GNNs) are successful at learning representations from most types of network data but suffer from limitations in large graphs, which do not have the Euclidean structure that time and image signals have in the limit. Yet, large graphs can often be identified as being similar to each other in the sense that they share structural properties. Indeed, graphs can be grouped in families converging to a common graph limit — the graphon. A graphon is a bounded symmetric kernel which can be interpreted as both a random graph model and a limit object of a convergent sequence of graphs. Graphs sampled from a graphon almost surely share structural properties in the limit, which implies that graphons describe families of similar graphs. We can thus expect that processing data supported on graphs associated with the same graphon should yield similar results. In my research, I formalize this intuition by showing that the error made when transferring a GNN across two graphs in a graphon family is small when the graphs are sufficiently large. This enables large-scale graph machine learning by transference: training GNNs on moderate-scale graphs and executing them on large-scale graphs.

CT3N Seminar: "Design of Targeted Antimicrobials" (Christopher A. Alabi)
2022-06-22 12:00 - 13:00 | Smilow 10th Floor, Room 146AB
This hybrid seminar is hosted by the Center for Targeted Therapeutics and Translational Nanomedicine (CT3N)

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PSOC@Penn Talk “Small fat droplets are sufficiently rigid to indent a nucleus, dilute the lamina, and cause rupture" (Irena Ivanoska)
2022-06-21 12:00 - 13:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Contact manu@seas.upenn.edu for the Zoom link.
Title: “Small fat droplets are sufficiently rigid to indent a nucleus, dilute the lamina, and cause rupture”

MEAM Seminar: "Mobile Wireless Infrastructure on Demand in Robot Teams"
2022-06-21 10:00 - 11:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
The promise of multi-robot systems is that they can complete tasks quicker and more efficiently than a single robot. However, such performance gains are only realized if robots can communicate with each other and coordinate their actions. As on-board autonomy advances, robots are increasingly being deployed in environments without existing wireless infrastructure and must rely instead on peer-to-peer or ad-hoc networks in order to exchange information. In these scenarios, control actions taken to complete the task objective often move robots out of direct communication range of one another, introducing a tension between task fulfillment and communication network maintenance. In this seminar, I will present my work towards eliminating this tension and enabling multi-robot teams to operate in challenging environments by using robots as mobile wireless infrastructure.
