Penn Engineering Events

ESE Fall Colloquium Seminar - "New Materials for Three Dimensional Ferroelectric Microelectronics"
2021-11-23 11:00 - 12:00 (America/New_York) | Zoom – Meeting ID 954 7393 2132, PA, United States
In the last decade, there have been major changes in the families of ferroelectric materials available for integration with CMOS electronics. These new materials, including Hf1-xZrxO2, Al1-xScxN, Al1-xBxN and Zn1-xMgxO, offer the possibility of new functionalities. This talk will discuss the possibility of exploiting the 3rd dimension in microelectronics for functions beyond interconnects, enabling 3D non-von Neumann computer architectures exploiting ferroelectrics for local memory, logic in memory, digital/analog computation, and neuromorphic functionality. This approach circumvents the end of Moore’s law in 2D scaling, while simultaneously overcoming the “von Neumann bottleneck” in moving instructions and data between separate logic and memory circuits. Computing accounts for 5 – 15% of worldwide energy consumption. In the U.S., data centers alone are projected to consume approximately 73 billion kWh in 2020. While recent efficiency gains in hardware have partially mitigated the rising energy consumption of computing, major gains are achievable in a paradigm shift to 3D computing systems, especially those that closely couple memory and logic. The talk will cover the relevant materials, their deposition conditions, and what is known about the wake-up, fatigue, and retention processes.

ESE Ph.D. Thesis Defense: "Computer-aided Clinical Trials for Medical Devices"
2021-11-22 15:30 - 17:00 | Zoom – Meeting ID 916 4694 2571
Life-critical medical devices require robust safety and efficacy to treat patient populations with
potentially large inter-patient and intra-patient variability. Today, the de facto standard for evaluating medical devices is the randomized clinical trial. However, even after years of device development many clinical trials fail. For example, in the Rhythm ID Goes Head to Head Trial (RIGHT) the risk for inappropriate therapy actually increased relative to control treatments.
With recent advances in physiological modeling and devices incorporating more complex software components, population-level device outcomes can be obtained with large-scale simulations. Consequently, there is a need to explore alternative approaches to evaluate devices within a clinical trial context.
This work presents a framework to utilize computer modeling and simulation to improve the evaluation of medical device software, such as the algorithms in implantable cardioverter defibrillators (ICD). Within this framework, virtual cohorts are generated and combined with real data to evaluate the efficacy of ICD algorithms while also quantifying the uncertainty due to the simulation. Results predicting the outcome of RIGHT and the improvement in statistical power while reducing the sample size are presented. Next, an approach to improving the performance of the device with Bayesian optimization is presented. Devices can degrade in performance when deployed to populations initially excluded in a clinical trial. For example, ICDs have shown increased rates of inappropriate therapy in patients with congenital heart disease. Bayesian optimization can be used to automate the adjustment of device parameters and fine-tune performance for a given cohort with minimal intervention. Our approach identifies parameters which improve the performance of the device with outcomes aligned with the Multicenter Automatic Defibrillator Implantation Trial–Reduce Inappropriate Therapy (MADIT-RIT) clinical trial.

PSOC@Penn Seminar: "Elucidating the role of cell-environment interactions in somatic cell acquisition of stemness” (Timothy L. Downing)
2021-11-22 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Room: Towne 225/Raisler Lounge
For zoom link, contact manu@seas.upenn.edu.

ODEI Spotlight: SWE Headshots on Smith Walk
2021-11-20 15:00 - 16:00 | PA
SWE Headshots | November 20, 3-4 pm | On Smith Walk (between Towne and Hayden Hall near the Penn Engineering Banner)
Come get a professional headshot taken on Saturday, November 20th (rain date Sunday, November 21st)! Headshots will be taking place on Smith Walk (between Towne and Hayden Hall near the Penn Engineering Banner) from 3-4pm.

MEAM PhD Thesis Defense: "High Throughput Immunospecific Detection and Analysis of Subcellular Nanomaterials at the Single Particle Level"
2021-11-19 13:30 - 14:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Extracellular vesicles (EVs) have shown great potential in diagnostics, therapeutics, and have been discovered to play a key role in intercellular communication. The study of EVs in biological fluids has proven challenging due to the nanoscale size of EVs (30 nm-1 µm diameter), the enormous quantity of EVs present in clinical samples (e.g. 10E10/mL), and the heterogeneous properties of EVs, even within those that originate from the same cell. My thesis has developed two distinct, but related, technologies to address these challenges.
The first half of my thesis focuses on isolation and interpretation of specific subsets of EVs from biological samples, such as plasma, based on particular expressions of surface proteins. From these isolated EVs we have demonstrated, across multiple diseases, that there are signatures of disease states encoded in the EV RNA cargo, which we identified using supervised machine learning. To this end, building on prior work from our group, we developed a multichannel nanofluidic system that could analyze crude clinical plasma samples with nanoscale precision, which was coined Track Etched Magnetic Nanopore (TENPO).
We evaluated the clinical potential TENPO by first applying it to diagnosing and staging pancreatic cancer, where current biomarkers have proven elusive to achieve sufficient sensitivity and specificity. In this work, we algorithmically combined tumor-associated EV mRNA and miRNA, isolated from plasma using TENPO, with ccfDNA levels, KRAS mutation detection, and CA19-9 via an ensemble machine learning model to form a multi-analyte panel. On an independent, blinded validation set (N = 136), we were able to distinguish patients with pancreatic cancer from those without at an accuracy of 92% (AUC=0.95). Moreover, among patients with pancreatic cancer, my model achieved significantly higher accuracy for disease staging (84%) than the current standard imaging method (64%). In addition to pancreatic cancer, I have also applied this approach to traumatic brain injury and to Alzheimer’s Disease to explored its diagnostic value in neurodegenerative diseases.
Though TENPO was successful in isolating specific subsets of EVs for downstream analysis, it was not able to resolve the heterogeneity that is known to exist between individual EVs. Current single EV analysis methods have also been exclusive to platforms that could only analyze a small number of EVs (< 20,000), limiting their ability to evaluate rare EV subsets due to subsampling error when searching for these rare EVs amongst the high EV background present in plasma. To address this challenge, I have developed a high throughput, droplet based optofluidic platform to quantify specific single EVs. The key innovation of my platform is parallelization of droplet generation, processing, and analysis to achieve a throughput >100x greater than typical in microfluidic systems, using only simple optics and accessible soft-lithography fabrication. I demonstrated that this improvement in throughput can be leveraged to quantify human neuron derived EVs at a limit of detection LOD = 13 EVs/µL, a >100x improvement over gold standard single EV characterization methods. Additionally, I demonstrated the potential of this system for use in clinical samples by detecting EVs in a complex media, containing up to 4,000 fold more background EVs, and achieved an LOD = 48 EVs/µL.
Beyond extracellular vesicles, I was also inspired to apply this immunospecific, nanoscale detection and analysis modality to other subcellular materials, namely mitochondria. I have developed a pipeline to isolate and amplify single mitochondrion DNA from individual cells with 20x higher yield than with conventional tools. With the improved yield, we were also able to reveal the pervasive single nucleotide variation on mitochondrion DNA within single cells. We also compared the genomic variation within neuron mitochondria versus that within astrocyte mitochondria, which is impossible via traditional methodology.

GRASP on Robotics: "Learning and Influencing Conventions in Interactive Robotics"
2021-11-19 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This will be a HYBRID Event with in-person attendance in Wu & Chen Auditorium and Virtual attendance via Zoom Webinar here.
There have been significant advances in the field of robot learning in the past decade. However, many challenges still remain when studying how robot learning can advance interactive agents such as robots that collaborate with humans, and how interactions can enable more effective robot learning. This introduces an opportunity for developing new robot learning algorithms that can help advance the science of interactive autonomy. In this talk, we will discuss a formalism that learns conventions, i.e., low-dimensional representations sufficient for capturing non-stationary interactions. We demonstrate how we can influence and stabilize these conventions to achieve desirable outcomes in multi-robot coordination. Finally, we will then talk about some of the challenges of learning such representations when interacting with humans, and how we can develop data-efficient techniques that can tap into different sources of data such as suboptimal demonstrations or can actively learn human preferences. We will end the talk with a discussion of applications of these techniques in assistive robotics.

BE Doctoral Dissertation Defense: "Novel design strategies for engineering biliverdin-binding fluorescent proteins" (Michael Magaraci)
2021-11-19 10:00 - 12:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Brian Chow are pleased to announce the Doctoral Dissertation Defense of Michael Magaraci.

Title: Novel design strategies for engineering biliverdin-binding fluorescent proteins

Date: Friday, November 19, 2021
Time: 10:00 AM (EST)
Location: Towne 337 and via Zoom at the link below:
https://upenn.zoom.us/j/98253474334?pwd=[REDACTED]

The public is welcome to attend.

MSE Thesis Defense: "Ultra-High-Resolution Patterning and Pattern Transfer via Nanocrystal Colloidal Lithography"
2021-11-18 15:30 - 16:30 | https://upenn.zoom.us/j/96715197752
The ability to design, pattern, and process materials at the nanoscale has enabled vast research opportunities ranging from fundamental science to technological applications and device integration. The continued development of nanoscience and nanotechnology relies upon pushing the limits of nanoscale fabrication capabilities. After decades of development, this frontier has moved to the sub-10 nm length scale to explore novel physical properties and functionalities for next-generation technology. However, conventional “top-down” strategies that have carried nanofabrication to this point have severe limitations for practically improving the resolution capabilities of deep nanoscale fabrication. In this dissertation, we demonstrate ultra-high-resolution patterning and pattern transfer using nanocrystal (NC) colloidal lithography. This innovative nanofabrication platform integrates bottom-up methods, that combine NC synthesis and self-assembly approaches, with well-established top-down techniques such as dry etching and thin film deposition.
We employ monodisperse NC building blocks with self-assembly methods to establish high-density, well-ordered patterns, where the inorganic core of each NC serves as a discrete hard mask used for high-fidelity pattern transfer into a desired substrate material. We demonstrate the use of isotropic NCs to establish various sub-10 nm pattern morphologies and examine the stability of the NC pattern upon dry etching, comparing NC monolayers and bilayers. We extend the NC colloidal lithography scheme using anisotropic NCs to demonstrate high-density, anisotropic pattern transfer into various substrate materials down to the sub-5 nm regime. The presented fabrication strategy offers further opportunities to leverage various combinations of NC morphologies and materials afforded by the extensive NC library for more complex pattern design. Additionally, this approach can be extended to process various substrate material classes at the deep nanoscale. The NC colloidal lithography platform enables broader access to single-digit nanoscale fabrication for the scientific community worldwide, which could impact various research sectors ranging from integrated circuits to memory devices, optoelectronics, metasurfaces, quantum devices and more.

BE Seminar: "Ionic Liquid-based Therapeutics" (Samir Mitragotri)
2021-11-18 15:30 - 16:30 | https://upenn.zoom.us/j/96715197752
This seminar will be held virtually on zoom – check your email for the link or contact ksas@seas.upenn.edu.
Ionic liquids, the liquid salts comprising organic anions and cations, offer exciting opportunities for several therapeutic applications. Their tunable properties offer control over their design and function. Starting with biocompatible ions, we synthesized a library of ionic liquids and explored them for various drug delivery applications. Ionic liquids provided unique advantages including overcoming the biological transport barriers of skin, buccal mucosa and the intestinal epithelium. At the same time, they also stabilized proteins and nucleic acids and enabled the delivery of biologics across these barriers. Ionic liquids also provided unique biological functions including adjuvancy towards vaccines and antimicrobial function. I will present an overview of the design features of ionic liquids and novel biomedical applications enabled by these unique materials.

ESE Ph.D. Thesis Defense: "Graph Convolutions for Teams of Robots"
2021-11-18 12:00 - 13:30 | Room 452 C, 3401 Walnut, 3401 Walnut Street, Philadelphia, PA, 19104, United States
In many applications in robotics, there exist teams of robots operating in dynamic environments requiring the design of complex communication and control schemes. The problem is made easier if one assumes the presence of an oracle that has instantaneous access to states of all entities in the environment and can communicate simultaneously without any loss. However, such an assumption is unrealistic especially when there exist a large number of robots. More specifically, we are interested in decentralized control policies for teams of robots using only local communication and sensory information to achieve high-level team objectives. We first make the case for using distributed reinforcement learning to learn local behaviors by optimizing for a sparse team-wide reward as opposed to existing model-based methods. A central caveat of learning policies using model-free reinforcement learning is the lack of scalability. To achieve large-scale scalable results, we introduce a novel paradigm where the policies are parametrized by graph convolutions. Additionally, we also develop new methodologies to train these policies and derive technical insights into their behaviors. Building upon these, we design perception-action loops for teams of robots that rely only on noisy visual sensors, a learned history state, and local information from nearby robots to achieve complex team wide-objectives. We demonstrate the effectiveness of our methods on several large-scale multi-robot tasks.

ODEI and SHPE Celebrate Hispanic and Native American Heritage
2021-11-17 16:30 - 17:30 | Quain Courtyard
On Wednesday November 17 at 4pm, Penn Engineering will celebrate the Hispanic/Native American Heritage. This celebration of our students, faculty and staff of Hispanic/Latinx, and Native American background is in support of our commitment to diversity and inclusion in the School. Dean Vijay Kumar will give welcome and opening remarks, followed by student and faculty speakers and cultural presentations by Penn Engineering Students. Food and refreshments will be served. This event is sponsored by ODEI, Grad. RAS, and SHPE.

CEMB Future Leaders Seminar: "A microviscosimetry toolbox for plant cells + tissue based on molecular rotors"
2021-11-17 11:00 - 12:00 | https://upenn.zoom.us/j/96715197752
Launched in May 2021, the Future Leaders in Mechanobiology is a monthly seminar series featuring up-and-coming leaders in mechanobiology–PhD students and postdocs from a wide range of fields, backgrounds, and institutions. By providing an international stage to share one’s work and opportunities to interact with researchers at all career stages, we aim to create an inclusive and valuable series for early-stage researchers and the mechanobiology community as a whole.
Register HERE for access to the Zoom link and visit the CEMB website for more information.

ESE 2021 Jack Keil Wolf Lecture - "MEMS: the Transition from “Four-Letter-Word” to “Trendy”"
2021-11-16 15:00 - 16:15 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Thirty years ago, semiconductor manufacturers (wafer fabs) rolled their eyes and muttered under their breath when they heard the word MEMS. Micro-Electromechanical Mechanical Systems are minute mechanical devices built on silicon integrated circuit wafers. They are the microphones, gravity sensors, oscillators, motion sensors, electronic filters in your cell-phone – and more. MEMS processes were “weird”. They required unusual and immature special processing tools and etch chemicals. MEMS wafers often broke inside traditional semiconductor processing tools, creating logistical nightmares for the wafer fabs. Packaging was a terrifying ordeal, protecting the miniscule mechanical structures from damage. Even as recently as 15 years ago, MEMS was considered a four letter word at the larger wafer fabs, or foundries. Today, that has all changed. Today, the largest foundries ALL manufacture MEMS devices and they scramble to be the supplier of the latest, newest MEMS invention. Today, MEMS special processing tools are all high precision, high-throughput, state-of-the-art equipment. Today, many options exist for packaging these bizarre, but powerful chips. Today, everyone wants to manufacture MEMS chips. Today, MEMS is “trendy”.
How did this happen? How did MEMS transition from an ugly, shunned, four letter status to being fashionable? My presentation will walk through this astonishing historical transformation, focusing on the revolutionary devices which are made possible by MEMS technology and how they have radically altered and augmented the way we interact with electronic systems.

PICS Alumni Spotlight: Dr. Xuran Wang, Postdoctoral Researcher at Carnegie Mellon University
2021-11-16 12:00 - 13:00 | Zoom – email kathom@seas.upenn.edu

MEAM Ph.D. Thesis Defense: "Flying Modular Robots: From Self-Assembling Structures in Midair to Embedding Grasping Capabilities"
2021-11-16 10:00 - 11:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Flying modular robots offer a suitable autonomous platform for multiple applications such as: search and rescue, cargo lifting, and object transportation. In addition, modular robots in a swarm can use their own bodies as building units to assemble large structures. This thesis introduces ModQuad, the self-assembly structure that can cooperatively fly based on autonomous modules. With these modules it is possible to assemble structures with rigid connections in multiple configurations. In contrast to related work, instead of assembling on the ground or on water, a midair approach to assemble structures is proposed. Docking modules in midair offer relevant advantages by the cost of the complexity to adapt the conglomerate controller at each docking step. Assembling structures in midair usually requires a relative localization system in between modules. A vision-based self-assembly method is proposed with structures composed of two modules. Scaling these flying modular robotic structures is a challenging problem usually limiting the benefits of modularity. A novel yaw actuation for quadrotor-based modules using individuals rolling angles by a one degree of freedom cage design is proposed for a more effective controllability around the structure z-axis. The resulting implementation enlarges the configuration space in a line configuration. Expanding the one degree of freedom cage design to arbitrary configurations allowed the development of algorithms capable of generating optimal and near-optimal configurations through a computational efficient search that first classifies and groups modules within the structure. Lastly, structures composed of non-rigid connections are explored leading the whole conglomerate to change its shape dynamically in-flight. Instead of adding extra components and mechanisms, versatility of modularity is utilized to embed grasping capabilities through a shape change addressed to a four-bar linkage configuration.

PSOC@Penn Seminar: "Cell Learning" (Jeremy Gunawardena)
2021-11-15 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

PICS Colloquium: "Molecular organization in biology: What can computer simulations teach us?"
2021-11-12 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Abstract: The formation of membraneless organelles (MLOs) via phase separation of proteins and nucleic acids has emerged as an essential process with which cells can maintain spatiotemporal control. Despite enormous progress in understanding the role of MLOs in biological function in the last ten years or so, the molecular details of the underlying phenomena are only beginning to emerge recently. We use computer simulations of coarse-grained and all-atom models to complement experimental studies to achieve insights into the molecular driving forces underlying biomolecular phase separation. In this talk, I’ll highlight results that demonstrate our approach’s usefulness for identifying general principles and system-specific insights into biomolecular structure and function. These results also open up new avenues for the design of biomaterials with tunable properties.

GRASP on Robotics: “Approaches to Grounded Language Acquisition from Human Interaction”
2021-11-12 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This will be a HYBRID Event with in-person attendance for Dr. Matuszek’s in-person talk in Wu & Chen Auditorium and Virtual attendance via Zoom Webinar here.
As robots move from labs and factories into human-centric spaces, it becomes progressively harder to predetermine the environments and interactions they will need to be able to handle. Letting robots learn from end users via natural language is an intuitive, versatile approach to handling novel situations robustly. Grounded language acquisition is concerned with learning to understand language in the context of the physical world. In this presentation, I will give an overview of our work on using joint statistical models to learn the grounded semantics of natural language describing an agent’s environment, and will describe work on applying those models in a sim-to-real language learning environment. I will also discuss the role of speech understanding in grounded language learning, including introducing a new dataset and results on learning directly from that speech.

Snack Break with ODEI and EngiQueers
2021-11-11 13:00 - 15:00 | Lobby and Mezzanine, Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Levine Lobby 11/11 from 1pm-3pm
ODEI and EngiQueers are collaborating to host a grab and go snack break, that showcases prominent LGBTQ+ individuals in STEM throughout history. Come grab a snack, and get a fact about a queer individual who played an integral role in the advancement of the STEM field and industry. While learning about queer folks who are making significant contributions to engineering, learn more about the LGBTQ+ resources that are available for Penn students. Representatives from ODEI, oSTEM, and EngiQueers would love to see you!

MSE Seminar: "Local to Meso-scale Order in Electronic Ceramics Characterized by Aberration -Corrected Scanning Transmission Electron Microscopy"
2021-11-11 12:30 - 13:30 | Auditorium, LRSM Building, 3231 Walnut Street, Philadelphia, PA, 19104, United States
The ability to design the composition and microstructure of electronic ceramics for emerging technological applications requires sophisticated characterization techniques that can provide quantitative information about local structure and chemistry. Such structure quantification is particularly important to the fundamental understanding of properties in many important non-linear dielectrics, where chemical heterogeneities associated with dopants or intrinsic lattice defects give rise to local inhomogeneities in charge, strain and polarization. Such local deviations from the global average structure and symmetry are linked to enhancements in macroscopic dielectric and electromechanical properties. This seminar discusses the use of aberration-corrected scanning transmission electron microscopy (STEM) to quantify short- and medium-range lattice disorder in electronic oxides, including ferroelectrics and relaxor ferroelectrics. The ability to quantify local structure on a sublattice basis and in real space provides unique insight into the structural complexities of these materials.

ESE Fall Colloquium Seminar - " Beyond Curve-Fitting: What’s next for deep learning in biomedical imaging?"
2021-11-11 11:00 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Over the last 5-10 years, deep learning has transformed biomedical imaging, from enhancing acquisition to maximizing downstream utility of scans. My research group has been at the forefront of this revolution, developing novel methods that have laid the foundation for next-generation tools. As I will describe in my talk, much of this progress relies on predictive models and thus can be viewed as “curve-fitting” with general-purpose models. I will then show a few examples of recent work from my group, where we move beyond the curve-fitting paradigm and custom build models in ways that allow us to gain novel insights, understand how the output was computed, or empower the end-user to choose the solution best suited for their needs. These examples will be from a range of applications, including MRI reconstruction, image registration, and neural encoding with fMRI data.

Fall 2021 GRASP SFI: "Artificial Intelligence and its Impact on Engineered-Systems Design"
2021-11-10 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This will be a HYBRID Event with in-person attendance in Levine 307 and Virtual attendance via Zoom here…
Our research employs artificial intelligence techniques that seek to automate the main time/cost drivers of engineered-systems design. The features of a system inform the form, function and behavior of the resulting concept that can be subsequently created using traditional manufacturing/additive manufacturing methods. While there exists a wide range of computer aided design tools that seek to generate 3D design concepts, they are primarily parametric in nature and rely extensively on domain expertise, which may not always be readily available. Grants from the National Science Foundation (NSF) and the Defense Advanced Research Projects Agency (DARPA) have enabled our research team to explore the use of Deep Generative Design methods such as Generative Adversarial Networks (GANs) to generate 3D representations of design concepts. However, there is more to a design than simply its 3D form, as the design must perform a function and operate in an environment where its behavior may/may not perform as intended. Towards this end, our research group has proposed liking the AI-generation of a design, with the automatic evaluation of its function and behavior using physics-based simulation engines. The end result is a physics-informed design that has the potential to be realized through techniques such as additive manufacturing.

CIS 189 Guest Lecture: "Optimization in Practice"
2021-11-09 17:15 - 18:15 | Towne 307, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
Discrete optimization plays a critical role in solving various resource allocation problems within the industry.
In this talk, we study problems from the two extremes of the optimization landscape; operational decision-making in real-time and resource provisioning for future considerations. Motivated by real-world business requirements ranging from load balancing in heterogeneous environments to privacy concerns and various service-level agreements, we demonstrate how constraint reasoning delivers effective solutions in both cases.
While solving large-scale problems is of great practical importance, we emphasize the need for solutions that are not only efficient but also flexible, easy to update and maintain. We show how Constraint Programming neatly suits the needs of such dynamic environments with continually changing requirements.

Towne 307 + Zoom
(Meeting ID: 945 8230 3285
Passcode: [REDACTED]

ESE Fall Colloquium Seminar - "2D Materials, from Academia to Industry"
2021-11-09 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Semiconductor sales will reach over $500 billion worldwide in 2021, a gigantic industry that keeps on growing with increasing demand for faster, more powerful, and smaller chips. However, as we keep scaling, the silicon (Si) transistor will soon reach its physical limit, and there is a pressing need to find an alternative post-Si material to enable the continuation of Moore’s Law.
In the early 2000s, scientists discovered that graphite could be exfoliated down into an atomic form, going from a 3D bulk material down to a 2D stable honeycomb lattice of carbon atoms called graphene. Scientists marveled at graphene’s astonishing electrical and mechanical properties, however, for all that graphene has to offer, it lacks a band gap that is essential for logic devices. This created a surge in research on materials beyond graphene, scientists searching for an elusive 2D material that would possess a bandgap to satisfy the need of the semiconducting industry. Monolayer Transition Metal Dichalcogenides (TMDs) possess the bandgap that graphene lacks, and with the vast variety of TMDs available, coupled with its encouraging electrical properties, make TMDs a promising candidate.
In this talk, I will present my years of research on 2D materials focusing on TMDs, from synthesis and characterization to innovative applications. I will demonstrate a scalable method for monolayer TMD growth and integration, its applications (e.g. opioid biosensor and flexible electronics), the first report of monolayer growth and electrical characterization of the topological 1T’-TMDs, and in-plane monolayer TMD heterostructures with different metal atoms or atomic phases. I will also discuss some of Intel’s industrial research to date on 2D materials, how TMDs and other 2D materials are finding their way into production and potentially into everyone’s day to day life.

MEAM Seminar: "Time and Rate Dependent Fracture of Polymer Gels and Interfaces"
2021-11-09 10:00 - 11:30 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Fracture of materials and interfaces is often time and rate dependent. The underlying mechanisms for the time and rate dependent fracture may include local molecular processes, viscoelasticity, and poroelasticity (solvent diffusion coupled with deformation). In this talk, I will present our recent works on two different mechanisms. First, the effects of poroelasticity on fracture of polymer gels will be discussed. A path-independent, modified J-integral approach is adopted to define the crack-tip energy release rate as the energetic driving force for crack growth in gels, taking into account the energy dissipation by solvent diffusion. For a stationary crack, the energy release rate is time dependent, with which delayed fracture can be predicted based on a Griffith-like fracture criterion. For steady-state crack growth in a long-strip specimen, the energy release rate is a function of the crack speed, with rate-dependent poroelastic toughening. With a poroelastic cohesive zone model, solvent diffusion within the cohesive zone leads to significantly enhanced poroelastic toughening as the crack speed increases. Second, for rate-dependent fracture of a polymer interface, we propose a multiscale cohesive zone model, considering the energetics of bond stretching, the entropic effect of long molecular chains, the kinetics of thermally activated chain scission, and statistical distributions of the chain lengths. This model relates the macroscopically measurable interfacial properties (toughness, strength, and traction-separation relations) to molecular structures of the interface, and the rate dependence results naturally from the kinetics of damage evolution as a thermally activated process. Finite element simulations with the cohesive zone model are directly compared to double cantilever beam experiments for rate-dependent fracture of a silicon/epoxy interface.

BE Dissertation Defense: "Versican/Collagen Interactions in Tissue Structure and Mechanics" (Dongning Chen)
2021-11-08 12:00 - 14:00 | BRB 253
The Department of Bioengineering at the University of Pennsylvania and Dr. Rebecca Wells are pleased to announce the Doctoral Dissertation Defense of Dongning Chen.

Title: Versican/Collagen Interactions in Tissue Structure and Mechanics
Date: Nov. 8, 2021
Time: 12pm

The public is welcome to attend in person at BRB 253 and via zoom: https://upenn.zoom.us/j/6088045110

PSOC@Penn Seminar: "High-throughput multi-dimensional T cell profiling enabled systems immunology" (Ning Jenny Jiang)
2021-11-08 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

PICS Colloquium: "From atoms to emergent mechanisms with information bottleneck and diffusion probabilistic models"
2021-11-05 14:00 - 15:00 | Zoom – email kathom@seas.upenn.edu
Abstract: The ability to rapidly learn from high-dimensional data to make reliable predictions about the future is crucial in many contexts. This could be a fly avoiding predators, or the retina processing terabytes of data guiding complex human actions. Modern day artificial intelligence (AI) aims to mimic this fidelity and has been successful in many domains of life. It is tempting to ask if AI could also be used to understand and predict the emergent mechanisms across timescales for complex molecules with millions of atoms. In this talk I will show that certain flavors of AI can indeed help us understand generic molecular structure and dynamics, and also predict it even in situations with arbitrary long memories. However this requires close integration of AI with old and new ideas in statistical mechanics. I will talk about such methods developed by my group (1-3) using information bottleneck, denoising probabilistic models and long short-term memory networks, focusing on the first one or two frameworks in interest of time. I will demonstrate the methods on different problems, where we predict mechanisms at timescales much longer than milliseconds while keeping all-atom/femtosecond resolution. These include ligand dissociation from flexible protein/RNA and crystal nucleation with competing polymorphs.
References:
1. Wang, Y., Ribeiro, J.M.L. & Tiwary, P. Past–future information bottleneck for sampling molecular reaction coordinate simultaneously with thermodynamics and kinetics. Nat. Commun. 10, 3573 (2019).
2. Wang, Y., & Tiwary, P. Denoising diffusion probabilistic models for replica exchange. arXiv preprint arXiv:2107.07369 (2021).
3. Tsai, S.T, Kuo, E.J. & Tiwary, P. Learning Molecular Dynamics with Simple Language Model built upon Long Short-Term Memory Neural Network. Nat. Commun. 11, 5115 (2020).

GRASP on Robotics: "Event-based Neuromorphic Perception and Computation: The Future of Sensing and AI"
2021-11-05 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This will be a HYBRID Event with in-person attendance in Wu & Chen Auditorium and Virtual attendance via Zoom Webinar here.
There has been significant research over the past two decades in developing new systems for spiking neural computation. The impact of neuromorphic concepts on recent developments in optical sensing, display and artificial vision is presented. State-of-the-art image sensors suffer from severe limitations imposed by their very principle of operation. These sensors acquire the visual information as a series of ’snapshots’ recorded at discrete point in time, hence time-quantized at a predetermined frame rate, resulting in limited temporal resolution, low dynamic range and a high degree of redundancy in the acquired data. Nature suggests a different approach: Biological vision systems are driven and controlled by events happening within the scene in view, and not — like image sensors — by artificially created timing and control signals that have no relation whatsoever to the source of the visual information. Translating the frameless paradigm of biological vision to artificial imaging systems implies that control over the acquisition of visual information is no longer being imposed externally to an array of pixels but the decision making is transferred to the single pixel that handles its own information individually. It is demonstrated that bio-inspired vision systems have the potential to outperform conventional, frame-based vision acquisition and processing systems in many application fields and to establish new benchmarks in terms of redundancy suppression/data compression, dynamic range, temporal resolution and power efficiency to realize advanced functionality like 3D vision, object tracking, motor control, visual feedback loops and even allow us to rethink our current paradigm of computation. The ultimate goal is to develop brain-inspired general purpose computation architectures that can breach the current bottleneck introduced by the von Neumann architecture.

ODEI Spotlight: Critical Race Theory and DEI: From Theory to Practice
2021-11-04 17:30 - 19:00 | https://upenn.zoom.us/j/96715197752
The African-American Resource Center & Office of Affirmative Action Presents:

Critical Race Theory and DEI: From Theory to Practice
Join us as we examine the language switch from Critical Race Theory to Diversity Equity and Inclusion,
and what each term means and what DEI means and looks like at Penn.

Zoom Link:
http://upenn.zoom.us/j/7443577924

Panelists:
Beverly A. Crawford, Director of Diversity and Inclusion, Department of Preventive and Restorative Sciences
Captain W. Nicole McCoy, Commanding Officer of Diversity, Equity, and Inclusion, Public Safety
Monica Monroe, Associate Dean for Equity & Inclusion, Carey Law School

Moderator:
Valerie Dorsey Allen, Director, African-American Resource Center

Keynote Speaker:
Chaz L. Howard, Penn’s Vice President for Social Equity and Community
