Penn Engineering Events

[VIRTUAL] Spring 2023 Robotics MSE Capstone Presentation
2023-05-04 16:00 - 16:30 (America/New_York) | https://upenn.zoom.us/j/96715197752
This is a virtual event via Zoom.
Zachary Block, Amar Mohanty, Keyan Zhai
Advised by Dr. Mark Yim
“Automated At-Home Fall Assessment for the Elderly Using Computer Vision”

Spring 2023 Robotics MSE Thesis Presentations
2023-05-05 12:30 - 16:00 | Towne 337
This is a hybrid event that will take place in Towne 337 and via Zoom.

12:30pm – Welcome Remarks
Dr. Ani Hsieh – ROBO Program Chair
12:35pm – Haoran Tang
Advised by: Dr. Pratik Chaudhari
“Navigating the Task Manifold”
1:05pm – Ankit Prabhu
Advised by: Dr. Vijay Kumar
“Robots in Timberland: Towards Fine-Grained Semantic Mapping by UAVs in Forests for Diameter Estimation”
1:35pm – Xiatao Sun
Advised by: Dr. Vijay Kumar
“Imitation Learning for Autonomous Quadrotor Flight“
2:05pm – Bo Wu
Advised by: Dr. Kostas Daniilidis
“The Role of Mapping in Modern Robot Navigation Tasks”
2:35pm – Maya Guru
Advised by: Rahul Mangharam
“Ethics and Liability Considerations of Autonomous Vehicle Driving Policies”

3:05pm – Jinxu Zhang
Advised by: Jianbo Shi
“Detection and Curation of Generated Images from Diffusion Model”
3:35pm – Kaihan Zhu (CIS)
Advised by: Jianbo Shi
“Experiment on Super Resolution Through UNet and Diffusion Transformer”

BE Doctoral Dissertation Defense: "Resident Macrophages in Tendon Growth and Development" (Catherine Bautista)
2023-05-08 10:00 - 12:00 | Class of 62 Auditorium, John Morgan Building, 3620 Hamilton Walk, Philadelphia, PA, 19104
The Department of Bioengineering at the University of Pennsylvania and Dr. Nathaniel Dyment are pleased to announce the Doctoral Dissertation Defense of Catherine Bautista.

Title: Resident Macrophages in Tendon Growth and Development
Date: May 8, 2023
Time: 10:00am
Location: JMB Class of ’62 Auditorium

Zoom: https://upenn.zoom.us/j/94981950758?pwd=TEdHN0FQU2MvMk52KzhaTTM0MWJvZz09

The public is welcome to attend.

2023 Heilmeier Award Lecture: Dr. Dani S. Bassett
2023-05-08 13:00 - 14:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
“On Being Curious”
What is curiosity? Is it an emotion? A behavior? A cognitive process? Curiosity seems to be an abstract concept — like love, perhaps, or justice — far from the realm of those bits of nature that science can possibly address. However, contrary to intuition, leading theories of curiosity from history, philosophy, and psychology are surprisingly amenable to formalization in an emerging branch of mathematics known as network science. Such a formalization allows theories of curiosity to be explicitly tested and validated in linguistic and behavioral data. In understanding the foundational processes of curiosity, we can turn to pressing societal questions that can only be addressed through interdisciplinary work that foregrounds a critical consciousness. How can we practice, mentor, and teach curiosity? In what ways might we value and support diverse curiosities? What is an ethical curiosity?

ESE PhD Thesis Defense: "Event-based Perception for Ground Vehicle Control"
2023-05-10 09:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Autonomous vehicles rely on environmental perception to inform the system on how to act. Vision sensors, such as conventional cameras, have been at the forefront of the perception of most mobile platforms. However, conventional cameras have limitations such as high data rates, low dynamic range, and high latency. Dynamic vision sensors, such as event cameras, address and overcome those shortcomings by recording changes in the logarithm of light intensity at pixel level asynchronously and independently. With the benefits of high dynamic range, low power consumption, low latency, and high temporal resolution, event cameras excel as vision sensors for autonomous ground vehicle applications. This dissertation highlights the use of event cameras to inform control decisions for autonomous ground vehicles. Additionally, it introduces a new 1/10th scale autonomous testing platform, Ryder.

BE Doctoral Dissertation Defense: "Engineering stem cells and organoids on a chip for the study of human health and disease" (Sunghee Estelle Park)
2023-05-10 13:00 - 15:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Dan Huh are pleased to announce the Doctoral Dissertation Defense of Sunghee Estelle Park.
Title: Engineering stem cells and organoids on a chip for the study of human health and disease
Date: Wednesday, May 10, 2023
Time: 1:00 pm
Location: Towne 225 Raisler Lounge
The public is welcome to attend.

MEAM Ph.D. Thesis Defense: "Aluminum Scandium Nitride (AlScN) Films for Microelectromechanical Systems"
2023-05-10 15:00 - 16:00 | Towne 307, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Advancements in wireless and sensor technology have resulted in increasing demand for piezoelectric MEMS devices in wireless handsets and base stations, automobile technology, health monitoring sensors, and environmental sensors. Due to its high-quality factor (Q), Young’s modulus, sound velocity, and low mechanical and dielectric losses, AlN is an advantageous resonator material with applications in radio frequency filtering. AlN’s low piezoelectric coefficients, however, limit its application, especially when large electromechanical coupling is required such as wide bandwidth acoustic filters and energy harvesters. In 2009 it was discovered that alloying AlN with Scandium (Sc) increases its d33 piezoelectric coefficient by over 500% and maintains compatibility with post-CMOS integration when deposited below 400∘{1}*C. As process parameters and Sc levels are modified to enhance performance, this also impacts the built-in stress in the film. Undesired stress can degrade device performance in thin films and cause undesired deformations in released MEMS structures. Undesired phases and anomalously oriented grains (AOGs) reduce piezoelectric coefficients, film orientation, and modify stress. AOGs also render etching of device structures problematic as the AOG regions etch at a much lower rate. AlScN theoretical material models do not capture these and other fabrication related effects and often fail to accurately predict the electromechanical properties of AlScN thin films.
This presentation will discuss the origins of stress and anomalous grain formation in AlScN physical vapor deposition processes, establish methods to control the stress, and inhibit anomalous grain growth over a range of scandium alloying levels to yield high quality AlScN films with large piezoelectric coefficients. The physical mechanism behind stress gradients in AlScN thin films and methods mitigate stress gradients to reduce out-of-plane deformations in released MEMS structures will also be discussed. I demonstrate a technique where the total process gas flow is varied during the deposition to compensate for the native through-thickness stress gradient in sputtered AlScN thin films. Finally, I will provide methods to extract the AlScN stiffness, piezoelectric, and permittivity tenors from MEMS structures carefully designed to isolate various electromechanical parameters. A suite of device structures capable of measuring the key electromechanical properties of AlScN materials as a function of Sc alloying are demonstrated. Extraction of electromechanical properties is performed by matching solutions using COMSOL Multiphysics Finite Element Solver with the measurements obtained from the suite of device structures. This presentation provides physical vapor deposition parameters to deposit low stress, stress gradient free, and AOG free AlScN films, fabrication processes to develop AlScN devices, as well as electromechanical material models with complete material parameters to predict device performance. These are crucial innovations enabling the realization of devices in Al1−xScxN thin films.
{1}*M. Akiyama, T. Kamohara, K. Kano, A. Teshigahara, Y. Takeuchi, and N. Kawahara. (2009). Enhancement of piezoelectric response in scandium aluminum nitride alloy thin films prepared by dual reactive cosputtering. Advanced Materials, 21(5), 593-596.

MSE David P. Pope Distinguished Lecture: "Intelligentsia of Nano-Architected Hierarchical Materials"
2023-05-11 11:30 - 12:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Creation of reconfigurable and multi-functional materials can be achieved by incorporating architecture into material design. In our research, we design and fabricate three-dimensional (3D) nano-architected materials that can exhibit superior and often tunable thermal, photonic, electrochemical, biochemical, and mechanical properties at extremely low mass densities (lighter than aerogels), which renders them useful and enabling in technological applications. Dominant properties of such meta-materials are driven by their multi-scale nature: from characteristic material microstructure (atoms) to individual constituents (nanometers) to structural components (microns) to overall architectures (millimeters and above).
The focus of this talk is on additive manufacturing via vat polymerization and function-containing chemical synthesis to create 3D nano- and micro-architected metals, ceramics, multifunctional metal oxides (nano-photonics, photocatalytic, piezoelectric, etc.), and metal-containing polymer complexes, etc., as well as demonstrate their potential in some real-use biomedical, protective, and sensing applications. I will describe how the choice of architecture, material, and external stimulus can elicit stimulus- responsive, reconfigurable, and multifunctional response.

Penn Engineering Commencement 2023: Doctoral Ceremony
2023-05-11 15:30 - 16:30 | Irvine Auditorium, 3401 Spruce Street, Philadelphia, PA, 19104, United States
Celebrate Penn Engineering’s 2023 Doctoral Graduates. Additional information is available on the Penn Engineering Commencement website.

ESE PhD Thesis Defense: "Control and Optimization over Large-Scale Networks"
2023-05-12 10:00 | Room 452 C, 3401 Walnut, 3401 Walnut Street, Philadelphia, PA, 19104, United States
The future of the Internet of Things (IoT) envisions very large networks of spatially distributed devices cooperating to solve common tasks in both industrial and urban environments. That vision fundamentally relies on the use of wireless communication across such networks to enable flexibility, mobility, and dynamic configurations. To help realize that vision, we discuss three related challenges in this dissertation. First, we present a constrained reinforcement learning framework for the joint design of control and communication policies in wireless control systems. As the scale of deployment of spatially distributed control systems grows, however, the performance of learned policies deteriorate. In the second part of this talk we then investigate the design of scalable and transferable resource allocation policies to govern communication in wireless control systems. We conclude the talk by generalizing that approach to large-scale distributed optimization problems and show that one can learn distributed optimization algorithms that match or exceed the performance of hand-crafted ones.

Penn Engineering Commencement 2023: Master's Ceremony
2023-05-12 14:00 - 16:30 | Palestra, 223 South 33rd Street, Philadelphia, PA, 19104, United States
Celebrate the Penn Engineering 2023 Master’s Graduates. Additional information is available on the Penn Engineering Commencement website.

Penn Engineering Portrait Celebration in Honor of Ms. Cora Ingrum and Ms. Donna Hampton
2023-05-13 09:30 - 10:15 | Heilmeier Hall (Room 100), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Dean Vijay Kumar invites members of the Penn Engineering community to attend the unveiling of commissioned portraits of:
Ms. Cora Ingrum
by Patricia Watwood
and
Ms. Donna Hampton
by Ashon Crawley
There will be a breakfast reception to follow.

Penn Engineering Commencement 2023: Undergraduate Ceremony
2023-05-13 14:00 - 16:00 | Palestra, 223 South 33rd Street, Philadelphia, PA, 19104, United States
Celebrate the Penn Engineering Undergraduate Class of 2023. Additional information is available on the Penn Engineering Commencement website.

Penn Engineering 2023 Commencement Open House
2023-05-15 12:00 - 14:00
Immediately following the University Ceremony, Penn Engineering will host an Open House for the School’s returning graduates and their families throughout the first floors of the main Engineering complex.
Included are photo booth opportunities, a t-shirt giveaway (including a live t-shirt press!), and light refreshments. Department offices will also be open as a location for graduates and their loved ones to connect one last time with staff and faculty. Please join us!
More information, including a map of departmental locations, is available here.

Physics PhD Thesis Defense: "Characterization of Solid State Defect Systems For Quantum Computing, Communication, and Sensing"
2023-05-16 10:00 | Towne 319, 220 S. 33rd Street, Philadelphia, 19104, United States
Solid state defects have emerged as a leading candidate for platforms in quantum computing, communication, and sensing. The electronic spins localized around these defects have many advantages such as room temperature coherence, spin dependent optical transitions which enable visible-wavelength initialization and readout, and resonant frequencies compatible with widely available off-the-shelf microwave hardware. Furthermore, the nuclear spins coupled to these electronic spins provide additional quantum registers which can be used as long-lived memories, ancilla qubits to enhance sensing and communication schemes based on the electronic spin, or for general purpose computation. However, unlike systems which are all identical, such as trapped atoms, or systems which are man-made, such as superconducting circuits, the formation and structure of defects, as well as their coupled nuclear spins, is stochastic and difficult to model using textit{ab initio} methods. This thesis focuses on methods to efficiently and precisely characterize the properties of these systems. After presenting sufficient background for a general scientific audience, a method is outlined for robustly and efficiently quantifying the optical properties of defect-based emitters, even if the emitters are heterogeneous. We show how this method can be used to study treatment effects in novel systems, such as hexagonal Boron Nitride (hBN), where a new class of defect-based emitters has been identified but proven difficult to characterize – largely due to the widely varying optical properties of emitters which are believed to arise from the same defect. We then describe the infrastructure developed within the laboratory to generate, run, and simulate the results of experiments such as those used in the remainder of the thesis. This is followed by an explanation of some of the state of the art techniques used to identify, control, and map the nuclear spins coupled to an electronic spin within a defect system. We then show how these techniques can be expanded to precisely measure the Hamiltonian parameters of a single nuclear spin – which opens the door to a new era where individual nuclear spins can be used to measure their environment and reveal information about the local molecular and crystal structure. Finally, this thesis concludes with a brief discussion of the ongoing work and future directions inspired by the ideas and work presented in this thesis.

MEAM Seminar: "Addressing Sensitivity-Induced Challenges in Modeling Rigid-Body Systems with Frictional Impacts"
2023-05-23 10:00 - 11:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Imperfect but useful physical models play a crucial role in planning and controlling robot locomotion and manipulation. However, as the field shifts toward complex real-world applications, model accuracy requirements are increasing while calibration data is becoming scarcer. Consequently, model inaccuracy or the sim2real gap often hinders the development of performant robotics algorithms. Frictional contact, the physical process driving these robotic tasks, exacerbates this issue. The motion of robots touching their surroundings is highly sensitive to initial conditions and material properties. Thus, even slight errors in state estimation and parameter identification can lead to significant prediction discrepancies. These challenges are amplified by the use of coarse rigid-body models, rather than high-fidelity solid mechanics, due to the faster-than-real-time computational requirements of robotics.
In this talk, we present two advancements towards accurate modeling of robotics undergoing contact. In the former, we discover how this sensitivity leads to poor training-time optimization landscapes and test-time generalization in common robotics modeling methods. Our method, ContactNets, circumvents both of these issues respectively with a novel statistics- and mechanics-inspired loss and implicit learning representations. ContactNets is capable of identifying geometric and frictional properties of an object rolling, pivoting, and sliding against its environment from just a handful of motion-captured trajectories. In the latter, we attribute sensitivity to the rapid ordering or sequencing of impact forces in nearly-simultaneous collisions—such as heel and toe strikes during a foot step. As existing rigid-body models lack the fidelity and accuracy to predict this ordering, we develop a set-valued rigid-body model which captures the set of all impact orderings as a continuous-time differential inclusion. We rigorously prove key theoretical properties of this model, including existence of solutions.

BE Doctoral Dissertation Defense: "Design, Modeling and Optimization of a Tape Spring Steerable Needle" (Omar Abdoun)
2023-05-26 11:30 - 13:30 | Towne 337
The Department of Bioengineering at the University of Pennsylvania and Dr. Mark Yim are pleased to announce the doctoral dissertation defense of Omar Abdoun.

Title: DESIGN, MODELING, AND OPTIMIZATION OF A TAPE SPRING STEERABLE NEEDLE

Date: 5/26
Time: 11:30am
Location: 337 Towne Building

Zoom is also an option. The Link Is below:

Omar Abdoun is inviting you to a scheduled Zoom meeting.

Topic: Omar Abdoun’s Thesis Defense
Time: May 26, 2023 11:30 AM Eastern Time (US and Canada)

Join Zoom Meeting
https://pennmedicine.zoom.us/j/93855309212

Meeting ID: 938 5530 9212

MEAM Seminar: "Progress on Templates for Spined and Tailed Legged Robots"
2023-05-30 10:00 - 11:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
By mirroring the success of biological systems, legged robots have the potential to be successful in almost every terrestrial environment. While legged machines have made significant advancements in the past 20 years, there still exists a considerable gap between what they can achieve and the abilities of animals. In this talk I’ll discuss some of my recent work on exploring how internal degrees of freedom – spines and tails – can help to create more agile robots. First I’ll discuss my recent results showing how an internal degree of freedom can enable gravity to energize a simple hopping robot using a novel stepping strategy. I’ll present my formal analysis of the system which explains how the strategy controls the distribution of energy in an intuitive manner and present simulation and hardware results showing our robot hopping at speeds of up to 8.85 leg lengths per second. Next I’ll present some new work where I show how a coupled oscillator model, traditionally used for studying vibrations, can explain the role of a spine in trotting and bounding.

ESE PhD Thesis Defense: "Compute-In-Memory on Emerging Memory Technology: From Device to Algorithm"
2023-05-30 14:00 - 16:00 | Room 313, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Current computing systems are mainly constructed on the von Neumann architecture, where data needs to be transferred to a processing unit from memory components. The latency associated with accessing data from the memory units is a key performance bottleneck for a range of data-intensive applications in the convergence of big data and AI. Several solutions have been proposed to mitigate and overcome this bottleneck, with a prominent one being placing memory and logic units in close physical proximity. While significant progress has been made along those lines at both technology and architecture levels, a transformative approach would be to implement arithmetic kernels precisely where the data are stored using memory devices. This is known as compute-in-memory (CIM).
In this dissertation, I will begin by presenting the most recent advancements in the CMOS-compatible ferroelectric memory technologies on aluminum nitride platform. Second, I will present a reconfigurable CIM system on field-programmable ferroelectric diodes in a transistor-free architecture, allowing for multiple essential data operations. Last, I will discuss the conceptualization and demonstration of a programmable parallel search architecture – analog content-addressable memory (ACAM) on complementary Si-CMOS ferroelectric field-effect-transistor memory. The deployment and acceleration of deep neural network and kernel regression on ACAM will also be presented.

MEAM Ph.D. Thesis Defense: "Transport Modeling and Design of Electrode Architectures for High Energy Density Batteries"
2023-05-31 09:00 - 10:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
With the ever-increasing production of portable electronics, internet of things devices, electric vehicles, unmanned aerial vehicles, and other autonomous robotic systems comes an increasing demand for reliable, long-lasting, portable power sources. Portable electronic systems are often limited by the energy density of the batteries that power them, and these batteries typically take up a large fraction of the overall device weight and volume. Higher energy density batteries are needed to effectively power current and future devices.
One strategy for increasing energy density is to increase the volume fraction of active materials in the battery by increasing the thickness and decreasing the porosity of the electrodes. However, existing electrode architectures cannot simultaneously enable thick, high-density electrodes because electrolyte pathways are necessary for ion transport. Creating high solid volume fraction electrodes requires new electrode architectures which enable ion transport even when electrolyte volume is limited.
To achieve high energy, most battery research focuses on making packaged batteries as small or as light as possible, irrespective of the systems that such batteries will power. In biology, multifunctional interconnected subsystems work together to create a more efficient full system. Incorporating multifunctionality into energy storage for robotics will lead to similar improvements in system-level efficiency.
This work demonstrates multiple approaches toward electrode architecture design for high energy density batteries. First, we demonstrate how continuous electrode architectures enabled by the electrodeposition of lithium cobalt oxide (LCO) can overcome electrolyte transport limitations via fast solid-state diffusion. These electrodeposited LCO cathodes create a large opportunity space for improved energy density by enabling thick, high solid volume fraction electrodes. We also present a novel catholyte architecture with the ability to store and extract energy from dissolved oxygen in silicone oil emulsions. This electrolyte is a promising candidate for multifunctional power systems and presents new design opportunities for flow batteries by removing the need for the challenging gas-liquid-solid interfaces and semi-open boundaries in conventional oxygen reduction reaction (ORR) cathodes.

CBE PhD Thesis Defense: "Modeling Diverse Processes at Oxide Interfaces"
2023-06-01 12:00 - 13:30 | Towne 225
In this thesis, ab initio methods including density functional theory are used in concert with molecular dynamics, enhanced sampling techniques, and microkinetic modeling to study oxide materials as applied to electrochemical ammonia synthesis, carbon mineralization, and the oxygen evolution reaction. Special attention is directed towards discussion of model selection and its relationship to the experimental system.

Perovskite oxide BaZrO3-based ceramic electrolytes are shown to favor migration of protons from the bulk to the surface followed by hydrogen evolution without the need for a recombination catalyst. Using this same BaZrO3 electrolyte model surface, microkinetic modeling of ammonia synthesis leads to the proposal of a new experimental methodology for improving selectivity to ammonia at elevated temperatures. The dissolution rates of Mg- and Ca-containing mineral oxides are shown to be surface dependent. Methods for calculating the lowest energy facets and terminations at different water chemical potentials are presented and discussed. Similarly, transition metal oxides under acidic oxygen evolution reaction conditions expose different facets and have different adsorbate coverages depending on material and reaction conditions. Activity and stability are intimately related to these condition-dependent changes. Multi-surface Pourbaix diagrams are presented that allow for targeting model systems that are most likely to compare well with experiment. To help reduce the inherent complexity of these materials, a model for predicting the hybridization energy due to interactions between adsorbates and metal oxide surfaces is presented pointing out the key electronic structure features dictating the strength of this adsorption interaction.

Agreement between theory and experiment for metal oxides depends strongly on model selection subject to the reaction environment constraints. Further insight can be gleaned from physical models such as the generalized concerted coupling model, which offers insights into how the oxide electronic structure can be tuned for an application.

MEAM Seminar: "Wall-modeled LES of 3-D Turbulent Boundary Layer with Emphasis on Grid Independency"
2023-06-05 10:00 - 11:00 | Room 2C4, David Rittenhouse Laboratory Building, 209 S. 33rd Street, Philadelphia, PA, 19143, United States
The capability to predict high-Reynolds-number turbulent flows is essential for many natural and engineering flows such as external aerodynamics (wind turbines, aircraft wings), hydrodynamics (the hull of marine vehicles) and atmospheric boundary-layer flow over complex landscapes and cityscapes. However, due to extreme disparity of scales present in high-Reynolds-number wall-bounded turbulent flows, any attempt to simulate these flows directly without resorting to modeling of some sort results in prohibitively large computational cost. Among various modeling paradigms, wall-modeled large-eddy simulation (WMLES) has the potential to be both predictive and affordable, capturing more of the complex flow physics in the outer portion of boundary layers while modeling the expensive inner layer.
In this talk, I will first present a comparative study of WMLES of a turbulent boundary layer with mean-flow three-dimensionality developing on the floor of a bent square duct, which mimics the flow over the swept wing of the aircraft. It is demonstrated that more complex wall models better predict the near-wall three-dimensionality. The wall-stress direction from the wall models is shown to have separable contributions from the equilibrium stress part and the integrated nonequilibrium effects, where how the latter is modeled differs among the wall models. Second, I will discuss the ill-defined notion of grid convergence in WMLES. I propose that the convergence rate of WMLES is controlled by the extent of the wall-modeled region. A new perspective here is that one may attempt to converge WMLES at the desired grid resolution, while the accuracy of the converged solution can be attributed primarily to wall models. Lastly, I will talk about a new perspective on the dynamic LES models for subgrid-scale closure. I will show that there are dynamically important directions along which dynamic models can be further optimized.

MEAM Seminar: “Computational Study on the Influence of Roughness at Low and Very-High Reynolds Numbers”
2023-06-06 10:00 - 11:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Many fluid problems of interest, such as turbulent flow over an airplane or transport processes in geophysical flows, contain wall-bounded regions that form boundary layers. Oftentimes, both numerical and experimental studies are simplified by using smooth surfaces. This simplification has allowed us to gain a greater understanding of near-wall processes for flows of engineering interest, yet most surfaces are inherently rough. In many cases, especially at higher Reynolds numbers, the roughness protrudes far enough into the boundary layer to disrupt the flow. This roughness can induce form drag, reducing efficiency for ships, planes, and turbines, or alter transport of particles in atmospheric flows. For lower Reynolds number flows, roughness may produce the opposite effect, reducing drag or enhancing lift capabilities. This is with the addition of dimples on a golf ball or the alula on a bird wing.
In this talk, I present numerical results on the effects of roughness at two opposite ends of the spectrum. At low Reynolds number (O(103)), roughness elements displayed an ability to decrease drag, reducing power required, and augment lift capabilities for a propeller designed for use with a micro-unmanned aerial vehicle. I discuss the physical mechanisms at play which influence near-wall vortical structures, enhancing the aerodynamics of the propeller in a particularly viscous regime. The results of the simulations are corroborated with an in-house experimental study. Next, I present preliminary simulation results to a very-high Reynolds number flow (O(106)) over a real topography featuring a step-change in roughness. An atmospheric boundary layer flow over the dunes at White Sands National Park in New Mexico is studied to discern the mechanism behind reduced sediment transport downstream of the step-change. I then discuss current efforts to explore how the internal boundary layer formed by the new wall condition may influence small near-wall scale interaction with large-scales in the outer portion of the flow.

MSE PhD Thesis Defense: Self-Healing and Shape Memory Metal Electrodes in Magnesium-and Lithium-Ion Batteries
2023-06-06 14:00 - 15:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States

Spring 2023 GRASP on Robotics: Pauline Pounds, The University of Queensland, "Drones, Bipeds and Sensors - 10 Years of the UQ Robotics Design Lab"
2023-06-09 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom. This week’s presenter will be in-person as well.

ABSTRACT
The Robotics Design Lab was founded in 2012 at the University of Queensland, Australia, and considers the holistic design of robots as a system. With the RDL Pauline Pounds’ work has focussed on improving robot performance, reducing cost, and developing practical solutions. Her work has sought to increase drone endurance, payload and range, as well as develop ultra-low cost self-deploying sensor systems. She has developed new sensors to allow drones to better sense and respond to aerodynamic conditions around them. Her latest work on bipeds seeks to enable affordable dynamical bipeds for commercial applications. This talk will give a broad overview of the last decade of her work in the RDL and highlight specific results within each of these areas.

MEAM Ph.D. Thesis Defense: "Manually-Operated, Slider Cassette for Multiplexed Molecular Detection at the Point of Care"
2023-06-09 13:00 - 14:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Personalized medicine requires the identification of disease-causing agents prior to prescribing therapy. Currently, molecular detection requires shipping bio samples to centralized laboratories. The time delay between sample collection and test results prevents health care givers from making timely, informed decisions. Furthermore, there is a shortage in centralized laboratories and trained technicians in resource poor settings such as rural areas and developing countries. To address this need for cost-effective, reliable, user-friendly, real-time, multiplexed detection of co-endemic pathogens at the point of need by minimally trained personnel, I propose a 3D-printed, manually operated, slider cassette for multiplexed molecular detection. All needed reagents (in dry form) and buffers are pre-stored in the cassette, refrigeration-free. Once the user introduces a raw sample such as whole blood into the cassette, the user pushes a sliding bar that contains a nucleic acid isolation membrane, comprised of chitosan coated glass fiber, through a sequence of unit operations. The slider’s motion actuates blisters that discharge, in sequence, lysis buffer, wash solution, and elution solution. The lysis process is assisted with heat incubation, wherein heat is provided by an exothermic reaction. Nucleic acids are isolated from the lysate through binding to the chitosan-coated membrane under low pH conditions. At the end of the sliding process, the nucleic acids are eluted with a high pH buffer and aliquoted by capillary forces to individual reaction chambers. Each chamber stores a pre-dried LAMP reaction mix specific to a target. The chambers are then incubated at 65C, facilitating LAMP amplification. The reaction products are detectable either in real time with fluorescent dye and/or at the end point with color change (colorimetric dye). A two-dimensional finite element (COMSOL) simulation was carried out to test for potential crosstalk among the reaction chambers and a three-dimensional finite element (FLUENT) simulation was performed to evaluate the on-cassette chemical heater’s performance used in the lysis process. I demonstrate the entire molecular diagnostic process from sample (plasma and blood) to answer by testing contrived samples spiked with various concentrations of HIV, HCV, and HBV.

MEAM Ph.D. Thesis Defense: "High Performance Electroadhesives for Materials and Robots with Electroprogrammable Stiffness"
2023-06-12 11:00 - 12:00 | Room 2C8, David Rittenhouse Laboratory Building, 209 South 33rd Street, Philadelphia, PA, 19104, United States
Materials with electroprogrammable stiffness and adhesion can enhance the performance of robotic systems, including prosthetics, medical devices, wearables, exoskeletons, and grippers. However, achieving large changes in stiffness and adhesive forces in real time is an ongoing challenge. Electroadhesive clutches can rapidly adhere high stiffness elements, although their low force capacities, high activation voltages, and inability to separate and turn off stiffness changes reliably have limited their applications.
A major challenge in realizing stronger electroadhesive clutches is that current parallel-plate models poorly predict clutch force capacity and cannot be used to design better devices. Thus, current electroadhesive clutches suffer from force capacities below that of other materials with an electrically-programmable stiffness. Furthermore, soft material interfaces have not been utilized for stronger electroadhesive clutches due to latent adhesion at the contact interface that prevents programmable release.
This work demonstrates strategies to improve electroadhesive clutch designs for high-performance applications in material systems and robots with an electrically-programmable stiffness. Using a fracture mechanics framework, we build an improved understanding of the relationship between clutch design, force capacity and contact area. This mechanics-based framework predicts clutch performance across multiple geometries and applied voltages. Based on this approach, a Coulombic electrostatic clutch with 63 times the force capacity per unit electrostatic force of state-of-the-art electroadhesive clutches is realized. By doing so with traditional dielectrics and electrode materials, we demonstrate the power of our mechanics-based design methodology to increase clutch performance without relying on expensive materials or intensive manufacturing processes, making our approach optimal for widespread adoption by robotics researchers.
Finally, this mechanics-based design methodology is applied to the design of clutches with soft material interfaces. We demonstrate that this approach in conjunction with an engineered electroadhesive surface enables the use of elastomeric materials and low-voltage ionoelastomers in electroadhesive clutches with increased force capacities, which are capable of programmable release at reduced device sizes. We utilize these high-performance clutch designs in novel applications with an electrically-programmable stiffness, including soft robotic hands with enhanced load carrying capacity, wearable haptic interfaces, and morphing fabrics.

5th Annual Learning for Dynamics & Control Conference
2023-06-14 - 2023-06-16 | University of Pennsylvania
Over the next decade, the biggest generator of data is expected to be devices that sense and control the physical world.
The explosion of real-time data that is emerging from the physical world requires a rapprochement of areas such as machine learning, control theory, and optimization. While control theory has been firmly rooted in the tradition of model-based design, the availability and scale of data (both temporal and spatial) will require rethinking the foundations of our discipline. From a machine learning perspective, one of the main challenges going forward is to go beyond pattern recognition and address problems in data-driven control and optimization of dynamical processes. Our overall goal is to create a new community of people who think rigorously across the disciplines, ask new questions, and develop the foundations of this new scientific area. We are happy to welcome you to the University of Pennsylvania for the 5th annual L4DC. Click here for more information.
Registration is now open!

MSE PhD Defense: Effects of Size and Composition on the Performance of Dealloyed Nanoporous Metal Catalysts for CO2 Reduction, O2 Evolution, and H2 Generation
2023-06-14 10:30 - 12:00 | LRSM Reading Room, 3231 Walnut St., Philadelphia, PA, 19104, United States

Department of Bioengineering Juneteenth Address: "A White Neighbor, a Black Surgeon, and a Mormon Computer Scientist Walk into a Bar…” (Kevin B. Johnson)
2023-06-14 11:00 - 12:00 | Berger Auditorium (Room 13), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
“A White Neighbor, a Black Surgeon, and a Mormon Computer Scientist Walk into a Bar…”
As we recognize Juneteenth, a holiday that brings awareness to what journalist Corey Mitchell calls “…a complex understanding of the nation’s past”, we also need to understand how many of our neighbors, staff, and faculty—even those born in the last 100 years—continue to navigate through the environment that made Juneteenth remarkable. Dr. Johnson will share a bit of his personal story and how this story informs his national service and passion for teaching.
This talk will be held live in person in Berger Auditorium (Skirkanich Hall basement), streamed on Zoom, and recorded.
Following the event, a limited number of box lunches will be available for in-person attendees. If you would like a box lunch, please RSVP here so we can get an accurate headcount.
Join Zoom Meeting
https://upenn.zoom.us/j/92503256013?pwd=amZKL1V0RUtYbnFjbHJEZXZEV01xZz09
Meeting ID: 925 0325 6013
Passcode: 801060
