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DTSTART;TZID=America/New_York:20220222T100000
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DTSTAMP:20260406T070932
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SUMMARY:MEAM Seminar: "Understanding Particulate Soft Materials: An Integrated Approach for Novel Energy and Environmental Solutions"
DESCRIPTION:Many industrial processes involve multiphase soft materials in which solid particles are dispersed or co-exists with a fluid phase and are therefore referred to as Particulate Soft Materials (PSMs). Examples can be found in many industries\, including food\, cosmetics\, pharmaceutical\, and energy\, as well as in natural settings\, e.g.\, soils and glaciers. PSMs often display a complex mechanical behavior that is characterized by features common to both viscous fluids and elasto-plastic solids\, with material properties that can change over time due to thermodynamic\, chemical or kinematic conditions. Consequently\, these complexities and our limited understanding of the behavior of PSMs can lead to critical industrial challenges\, ranging from quality control of concrete to shelf-life of consumer products. These issues can also prove environmentally disastrous\, as in the case of clogged subsea pipelines or in landslides and avalanches. Such problems call for immediate solutions to measure and model the PSM overall mechanical behavior\, towards an improved understanding of this vast class of materials and corresponding processes. \nMy research demonstrates that these challenges can be overcome by: (i) introducing novel experimental tools and protocols that allow us to study the mechanical and rheological response of PSMs\, even when their behavior is rapidly changing\, or mutating\, in time; and (ii) rigorously setting sound theoretical frameworks that explain the experimental observations. In this talk\, focusing on two PSMs that are of interest to the energy industry (i.e.\, paraffin gels and hydrate suspensions)\, I will introduce an example of the integrated experimental and theoretical framework that can successfully capture PSM complex visco-plastic response. As I will demonstrate in my talk\, this powerful approach not only improves our understanding of both artificial and natural PSMs\, but also provides guidelines to develop superior materials for critical energy and environmental challenges.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-understanding-particulate-soft-materials-an-integrated-approach-for-novel-energy-and-environmental-solutions/
LOCATION:Zoom – Email MEAM for Link\, peterlit@seas.upenn.edu
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220222T110000
DTEND;TZID=America/New_York:20220222T120000
DTSTAMP:20260406T070932
CREATED:20220216T145905Z
LAST-MODIFIED:20220216T145905Z
UID:10007087-1645527600-1645531200@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Towards Fair and Efficient Machine Learning with Large Models"
DESCRIPTION:Deep networks often achieve better accuracy as we employ larger models. However\, modern machine learning applications involve multiple considerations alongside accuracy\, such as resource-efficiency\, robustness\, or fairness. Deploying ML in the real-world requires sound solutions addressing these considerations. \nIn this talk\, I will first discuss optimizing fairness objectives for imbalanced data. We observe that a large model can easily achieve “perfect fairness” on training data but dramatically fail at the test-time due to overfitting. To address this\, we propose two strategies\, (1) A new family of fairness-seeking loss functions\, (2) Algorithms that optimize validation (rather than training) objective\, and combine them to achieve state-of-the-art performance. We also introduce new optimization methods that extend these to decentralized settings. \nI will then discuss training efficient sparse models. While conventional wisdom strongly advocates the use of regularization\, we observe that perfectly fitting a large model to data and then pruning it achieves stellar accuracy. We demystify this surprising feature-selection ability through a flexible theory which can answer “How good is the pruned model?”. \nIn summary\, our results provide several insights on learning with large models: (1) Our theory based on linear and random-feature models provide useful intuitions for understanding modern deep learning\, (2) Large models can benefit from unconventional training strategies such as new loss functions\, and (3) Validation phase is particularly helpful for large models that are susceptible to overfitting.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-towards-fair-and-efficient-machine-learning-with-large-models/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220222T153000
DTEND;TZID=America/New_York:20220222T163000
DTSTAMP:20260406T070932
CREATED:20220208T210700Z
LAST-MODIFIED:20220208T210700Z
UID:10007075-1645543800-1645547400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Modern Fine-grained Algorithms for Classic Problems"
DESCRIPTION:How fast can we solve or approximate classic problems that are known to admit a polynomial time solution? Often times the existing polynomial time algorithms are slow for practical applications. Fine-grained algorithm design aims to better understand the computational complexity of these problems and illustrates tradeoffs between the runtime of the algorithms and the quality of their solutions.\n\nIn this talk\, I will present my work on classic and fundamental problems in fine-grained complexity including edit distance\, longest common subsequence\, pattern matching\, longest increasing subsequence\, and knapsack. In particular\, my talk will cover an algorithm that approximates edit distance within a constant factor in truly subquadratic time. This answers a well-known question in combinatorial pattern matching.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-modern-fine-grained-algorithms-for-classic-problems/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220223T110000
DTEND;TZID=America/New_York:20220223T120000
DTSTAMP:20260406T070932
CREATED:20220211T150239Z
LAST-MODIFIED:20220211T150239Z
UID:10007084-1645614000-1645617600@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Quantum Many-Body Physics in the NISQ Era"
DESCRIPTION:Rapid progress in quantum computing technologies is ushering in a new era for quantum many-body physics. Today’s noisy\, intermediate-scale quantum (NISQ) devices\, while still far from fault-tolerant quantum computers\, are exceptional laboratory systems\, with large many-body Hilbert spaces and unprecedented capabilities for control and measurement. This allows the exploration of quantum dynamics in new far-from-equilibrium regimes\, and motivates new paradigms of phase structure. In this talk I will focus on two such paradigms: eigenstate-ordered phases in periodically driven systems\, and entanglement phases in “monitored” systems\, whose dynamics include projective measurements alongside unitary operations. As an example of the former\, I will discuss the realization of a “discrete time crystal” (DTC) on Google Quantum AI’s Sycamore processor\, focusing on the conceptual challenges involved in detecting the DTC’s signature eigenstate order despite intrinsic limitations of NISQ hardware. I will then present a new window into measurement-induced entanglement phases based on the idea of space-time duality: a transformation that relates unitary and monitored circuits by exchanging the roles of space and time in the dynamics\, which can be implemented on digital quantum simulators through a generalized “quantum teleportation” protocol.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-quantum-many-body-physics-in-the-nisq-era/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220223T150000
DTEND;TZID=America/New_York:20220223T160000
DTSTAMP:20260406T070932
CREATED:20220218T161426Z
LAST-MODIFIED:20220218T161426Z
UID:10007090-1645628400-1645632000@seasevents.nmsdev7.com
SUMMARY:Spring 2022 GRASP SFI: Marc Finzi\, New York University\, "Embedding Symmetries and Conservation Laws in Deep Learning Models for Dynamical Systems"
DESCRIPTION:*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom \nIn contrast to traditional control systems where detailed dynamics models are constructed from a mix of physical understanding and empirical data\, machine learning for intuitive physics\, reinforcement learning\, and robotics often takes a hands off approach treating the dynamics as a black box with little to no assumed structure. We show how desirable high level properties like symmetries\, energy and momentum conservation\, and other constraints can be reintroduced into these models to improve generalization. These high level attributes represent prior knowledge about the underlying physics of the system in the Bayesian sense\, and can even be incorporated in a way that does not limit the flexibility of the model.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-marc-finzi-new-york-university-embedding-symmetries-and-conservation-laws-in-deep-learning-models-for-dynamical-systems/
LOCATION:Levine 512
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220223T153000
DTEND;TZID=America/New_York:20220223T163000
DTSTAMP:20260406T070932
CREATED:20220113T034509Z
LAST-MODIFIED:20220113T034509Z
UID:10007010-1645630200-1645633800@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: “Beyond Ethanol: A Process and Systems Engineering Framework for the Design of Advanced Biofuels”
DESCRIPTION:Abstract \nIn my talk\, I will present my work on the application of process and systems engineering techniques to the design of integrated biorefineries that produce middle distillates (jet fuel and diesel). Unlike gasoline\, demand for middle distillates is expected to increase over the next 30 years\, and electrification and decarbonization of sectors where middle distillates are used (such as aviation and freight) is challenging. Biofuels offer a potentially sustainable alternative\, with the upgrading of ethanol to diesel and jet fuel being especially attractive. The ethanol upgrading platform has several advantages: (1) it can make use of available infrastructure; (2) it can be used to produce fuels over the whole distillation spectrum; and (3) it offers multiple chemical alternatives\, enabling the possibility of tailoring the properties of the fuels produced. \nDespite its advantages\, designing an optimal ethanol upgrading strategy is challenging\, as it requires the integration of three different areas: catalysis\, process synthesis\, and fuel property modeling. The challenges associated with the formulation of a framework integrating these areas\, coupled with the large design space characteristic of the problem\, have led scientists to rely on ad hoc approaches. In contrast\, in this talk\, the systematic design of ethanol upgrading biorefineries based on superstructure optimization will be discussed. Four fundamental questions will be addressed: (1) What are the energy requirements associated with the production of middle distillates? (2) What is the interplay among fuel properties\, economics\, and processes? (3) What is the relationship among biorefinery complexity\, processes\, and the fuels obtained? and (4) What is the ability of the advanced fuels identified in this work to satisfy fuel demand and mitigate CO2 emissions?
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-beyond-ethanol-a-process-and-systems-engineering-framework-for-the-design-of-advanced-biofuels/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220223T153000
DTEND;TZID=America/New_York:20220223T163000
DTSTAMP:20260406T070932
CREATED:20220211T010712Z
LAST-MODIFIED:20220211T010712Z
UID:10007078-1645630200-1645633800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Firm Foundations for Private Machine Learning and Statistics"
DESCRIPTION:How can researchers use sensitive datasets for machine learning and statistics without compromising the privacy of the individuals who contribute their data?  In this talk I will describe my work on the foundations of differential privacy\, a rigorous framework for answering this question.  In the past decade\, differential privacy has gone from largely theoretical to widely deployed\, and a theme of the talk will be how new deployments are forcing us to revisit foundational questions about differential privacy.  This talk will cover a range of issues from the fundamental—like optimal private statistical inference—to the applied—like auditing differentially private machine learning.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-firm-foundations-for-private-machine-learning-and-statistics/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220224T110000
DTEND;TZID=America/New_York:20220224T120000
DTSTAMP:20260406T070932
CREATED:20220222T131917Z
LAST-MODIFIED:20220222T131917Z
UID:10007099-1645700400-1645704000@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Provably Robust Algorithms for Prediction and Control"
DESCRIPTION:Feedback-driven decision-making systems are at the emerging frontier of machine learning applications. Upcoming applications of societal consequence\, such as self-driving vehicles and smartwatch-based health interventions\, have to contend with the challenge of operating in reactive stateful environments. In this talk\, I will describe my work on designing principled robust algorithms for feedback-driven learning\, with provable guarantees on computational and statistical efficiency. \nFirst\, I will introduce an efficient instance-optimal algorithm for control in the presence of adversarial disturbances. Beyond the realm of both stochastic and robust control\, such a data-driven notion of optimality combines worst-case guarantees with a promise of exceptional performance on benign instances. Moving on to prediction\, I will present a computationally and statistically efficient forecasting strategy for latent-state dynamical systems exhibiting long term dependencies\, mitigating the statistical challenge of learning with correlated samples\, and the computational difficulties associated with a non-convex maximum likelihood objective. To conclude\, I will discuss some practically relevant fundamental questions at the intersection of machine learning\, optimization\, and control that have the potential to unlock real progress in downstream applications.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-provably-robust-algorithms-for-prediction-and-control/
LOCATION:Zoom – Meeting ID 958 3045 4776
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220224T153000
DTEND;TZID=America/New_York:20220224T163000
DTSTAMP:20260406T070932
CREATED:20220211T012014Z
LAST-MODIFIED:20220211T012014Z
UID:10007079-1645716600-1645720200@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Learning to Generate Data by Estimating Gradients  of the Data Distribution"
DESCRIPTION:Generating data with complex patterns\, such as images\, audio\, and molecular structures\, requires fitting very flexible statistical models to the data distribution. Even in the age of deep neural networks\, building such models is difficult because they typically require an intractable normalization procedure to represent a probability distribution. To address this challenge\, I propose to model the vector field of gradients of the data distribution (known as the score function)\, which does not require normalization and therefore can take full advantage of the flexibility of deep neural networks. I will show how to (1) estimate the score function from data with flexible deep neural networks and principled statistical methods\, (2) generate new data using stochastic differential equations and Markov chain Monte Carlo\, and even (3) evaluate probabilities as in a traditional statistical model. The resulting method\, called score-based generative modeling\, achieves record-breaking performance in applications including image synthesis\, text-to-speech generation\, time series prediction\, and point cloud generation\, challenging the long-time dominance of generative adversarial networks (GANs) on many of these tasks. Furthermore\, unlike GANs\, score-based generative models are suitable for Bayesian reasoning tasks such as solving ill-posed inverse problems\, and I have demonstrated their superior performance on examples like sparse-view computed tomography and accelerated magnetic resonance imaging. Finally\, I will discuss how score-based generative modeling opens up new opportunities and new future research directions for building better machines to create and understand complex data in various disciplines of science and engineering.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-learning-to-generate-data-by-estimating-gradients-of-the-data-distribution/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220225T100000
DTEND;TZID=America/New_York:20220225T110000
DTSTAMP:20260406T070932
CREATED:20220217T164449Z
LAST-MODIFIED:20220217T164449Z
UID:10007089-1645783200-1645786800@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Microfluidic Devices with Capillary Circuits for User-friendly\, Low-cost\, Multiplexed Point-of-care\, Molecular Diagnostics"
DESCRIPTION:Rapid\, sensitive\, and specific detection is key to personalized medicine and to the prompt implementation of appropriate mitigation measures to reduce disease transmission\, mortality\, morbidity\, and cost. Conventional molecular detection methods require trained personnel and specialized laboratories\, which limits their use to centralized laboratories. Microfluidics enables point-of-care testing. \nIn this talk\, I will show how capillary circuits help automate liquid-distribution and sealing processes and eliminate the need for expensive equipment and highly skilled personnel. Next\, I will present two examples of fully 3D-printed microfluidic devices with capillary valves that were designed\, respectively\, for single-stage and two-stage\, multiplexed isothermal molecular detections of human\, animal\, and plant diseases.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-microfluidic-devices-with-capillary-circuits-for-user-friendly-low-cost-multiplexed-point-of-care-molecular-diagnostics/
LOCATION:Zoom – Email MEAM for Link\, peterlit@seas.upenn.edu
CATEGORIES:Seminar,Doctoral
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220225T103000
DTEND;TZID=America/New_York:20220225T114500
DTSTAMP:20260406T070932
CREATED:20220221T195817Z
LAST-MODIFIED:20220221T195817Z
UID:10007098-1645785000-1645789500@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: Jia Deng\, Princeton University\, “Toward Dense 3D Reconstruction in the Wild”
DESCRIPTION:This seminar will be held in person in Wu and Chen Auditorium as well as virtually via Zoom. \nReconstructing depth and motion of every pixel for arbitrary scenes is a core problem in 3D vision with many downstream applications. In this talk\, I will describe some of our recent efforts toward this goal\, including various strategies to obtain effective training data for single-image 3D reconstruction\, and new neural architectures that advance the state of the art of multiview 3D reconstruction.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-jia-deng-princeton-university-toward-dense-3d-reconstruction-in-the-wild-2/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220225T140000
DTEND;TZID=America/New_York:20220225T150000
DTSTAMP:20260406T070932
CREATED:20211109T145824Z
LAST-MODIFIED:20211109T145824Z
UID:10006962-1645797600-1645801200@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium "Driving physics of inverted flag flapping"
DESCRIPTION:Abstract: Fluid-structure interaction (FSI) is ubiquitous in the natural and engineered world\, and a better understanding of FSI systems can aid in the design of renewable energy harvesting technologies\, bio-inspired propulsion vehicles\, and biomedical devices (to name a few applications). In this talk we will investigate “inverted” flag flapping\, in which the flag is clamped at its trailing edge with respect to the incoming uniform flow. This canonical system exhibits a diverse range of behavioral regimes\, including flapping with amplitudes comparable to the flag length\, making it promising for energy harvesting. We will identify the physical mechanisms responsible for the onset of flapping\, the role of vortex shedding in flapping\, and the chaotic flapping regime that the system undergoes for different parameters. We will also characterize the effect of nonuniform flexibility in the dynamics of this beautiful FSI system\, and discuss some efforts for reduced-order modeling of these varied behaviors.
URL:https://seasevents.nmsdev7.com/event/pics-colloquium-driving-physics-of-inverted-flag-flapping/
LOCATION:Zoom – email kathom@seas.upenn.edu
CATEGORIES:Colloquium
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220228T120000
DTEND;TZID=America/New_York:20220228T130000
DTSTAMP:20260406T070932
CREATED:20220131T131236Z
LAST-MODIFIED:20220131T131236Z
UID:10007046-1646049600-1646053200@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: Leyuan Ma\, PhD
DESCRIPTION:Physical Sciences in Oncology Center PSOC@Penn \nSpring 2022 Hybrid-Seminar Series \nTowne 225 / Raisler Lounge @ Noon (EST) \nFor Zoom link \, please contact manu@seas.upenn.edu
URL:https://seasevents.nmsdev7.com/event/psocpenn-seminar-leyuan-ma-phd/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Faculty
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220228T153000
DTEND;TZID=America/New_York:20220228T163000
DTSTAMP:20260406T070932
CREATED:20220211T014526Z
LAST-MODIFIED:20220211T014526Z
UID:10007080-1646062200-1646065800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "On the Foundations of the Next-Generation Quantum Software System"
DESCRIPTION:The software system is one essential and critical component in a quantum computing system. However\, existing quantum software infrastructures are mainly designed for small-scale quantum computers while they cannot effectively accommodate large-scale quantum computing systems. In this talk\, I will first summarize the challenges in designing quantum software systems as the sizes of quantum computer systems continue to grow. Then I will show how we can overcome this grand scalability challenge by leveraging the power of high-level operators in various important tasks\, including quantum compiler optimization\, quantum program testing\, and so on. In the end\, I will briefly introduce my work on quantum software-hardware co-design and conclude my talk with future research opportunities.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-on-the-foundations-of-the-next-generation-quantum-software-system/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220301T100000
DTEND;TZID=America/New_York:20220301T113000
DTSTAMP:20260406T070932
CREATED:20220211T142802Z
LAST-MODIFIED:20220211T142802Z
UID:10007083-1646128800-1646134200@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Unknown Unknowns in Designing Porous Intercalation Electrodes for Batteries"
DESCRIPTION:Many batteries\, including the state-of-the-art Lithium-ion technology\, use porous intercalation electrodes. In such electrodes\, energy is stored in the form of ions intercalating in particles. The conventional approach to designing such electrodes relies on using the porous electrode theory to upscale particle-scale behavior to the electrode-scale response. In this talk\, I will discuss unusual material effects that obfuscate such a connection and can considerably change the design guidelines. Understanding these effects is critical to building lithium-ion batteries for new applications like extreme fast charging and electric flight as well as enabling batteries with new intercalation hosts.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-unknown-unknowns-in-designing-porous-intercalation-electrodes-for-batteries/
LOCATION:Zoom – Email MEAM for Link\, peterlit@seas.upenn.edu
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220301T110000
DTEND;TZID=America/New_York:20220301T120000
DTSTAMP:20260406T070932
CREATED:20220223T141705Z
LAST-MODIFIED:20220223T141705Z
UID:10007100-1646132400-1646136000@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Bridging Safety and Learning in Human-Robot Interaction"
DESCRIPTION:From autonomous cars in cities to mobile manipulators at home\, robots must interact with people. What makes this hard is that human behavior—especially when interacting with other agents—is vastly complex\, varying between individuals\, environments\, and over time. Thus\, robots rely on data and machine learning throughout the design process and during deployment to build and refine models of humans. However\, by blindly trusting their data-driven human models\, today’s robots confidently plan unsafe behaviors around people\, resulting in anything from miscoordination to dangerous collisions. \nMy research aims to ensure safety in human-robot interaction\, particularly when robots learn from and about people. In this talk\, I will discuss how treating robot learning algorithms as dynamical systems driven by human data enables safe human-robot interaction. I will first introduce a Bayesian monitor which infers online if the robot’s learned human model can evolve to well-explain observed human data. I will then discuss how a novel\, control-theoretic problem formulation enables us to formally quantify what the robot could learn online from human data and how quickly it could learn it. Coupling these ideas with robot motion planning algorithms\, I will demonstrate how robots can safely and automatically adapt their behavior based on how trustworthy their learned human models are. I will end this talk by taking a step back and raising the question: “What is the ‘right’ notion of safety when robots interact with people?” and discussing opportunities for how rethinking our notions of safety can capture more subtle aspects of human-robot interaction.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-bridging-safety-and-learning-in-human-robot-interaction/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220301T153000
DTEND;TZID=America/New_York:20220301T163000
DTSTAMP:20260406T070932
CREATED:20220217T010143Z
LAST-MODIFIED:20220217T010143Z
UID:10007088-1646148600-1646152200@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Neural Representation and Rendering of 3D Real-world Scenes"
DESCRIPTION:High-quality reconstruction and photo-realistic rendering of real-world scenes are two important tasks that have a wide range of applications in AR/VR\, movie production\, games\, and robotics. These tasks are challenging because real-world scenes contain complex phenomena\, such as occlusions\, motions and interactions. Approaching these tasks using classical computer graphics techniques is a highly difficult and time-consuming process\, which requires complicated capture procedures\, manual intervention\, and a sophisticated global illumination rendering process. In this talk\, I will introduce our recent work that integrates deep learning techniques into the classical graphics pipeline for modelling humans and static scenes in an automatic way. Specifically\, I will talk about creating photo-realistic animatable human characters from only RGB videos\, high-quality reconstruction and fast novel view synthesis of general static scenes from RGB image inputs\, and scene generation with a 3D generative model. Finally\, I will discuss challenges and opportunities in this area for future work.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-neural-representation-and-rendering-of-3d-real-world-scenes/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220302T150000
DTEND;TZID=America/New_York:20220302T160000
DTSTAMP:20260406T070932
CREATED:20220301T164637Z
LAST-MODIFIED:20220301T164637Z
UID:10007106-1646233200-1646236800@seasevents.nmsdev7.com
SUMMARY:Spring 2022 GRASP SFI: Ted Xiao\, Robotics at Google\, "A Panorama of End-to-end Robot Learning"
DESCRIPTION:In recent years\, a variety of approaches to robotic control have gained popularity as robots play an increasingly larger role in our everyday lives. In this talk I will give an introduction to modern-day robot learning\, covering engineering and research challenges. After establishing the foundations of popular methods\, I will present why I believe that end-to-end Machine Learning is the scalable approach for solving robotics problems. Finally\, I will talk about some interesting open problems and how data-driven methods can learn efficiently in the real world on a large set of tasks with less supervision.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-ted-xiao-university-of-california-berkeley-a-panorama-of-end-to-end-robot-learning/
LOCATION:Levine 512
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220302T153000
DTEND;TZID=America/New_York:20220302T163000
DTSTAMP:20260406T070932
CREATED:20220114T040056Z
LAST-MODIFIED:20220114T040056Z
UID:10007014-1646235000-1646238600@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Spying on Sugar Transporters: Kinetic Studies of Biomolecular Sensors"
DESCRIPTION:Abstract \nThe allocation of sugars from photosynthetic leaves to storage tissues in seeds\, fruits\, and tubers is an essential determinant of crop yields. In plants\, transporters play critical roles in allocating carbon to different organs. Transgenic modifications of plant membrane transporters have been shown to enhance crop yield and increase plants’ resistance to biotic and abiotic stresses. Yet\, quantitative\, systems-level models to support this effort are lacking. \nRecently\, biosensors gained traction for collecting spatio-temporally resolved information on cell physiology and to validate computational models. In this talk\, we report the design and use of genetically encoded biosensors to measure the activity of SWEETs\, the only known family of sugar transporters that facilitate the cellular release of sugar in plants. We created a SweetTrac sensor by inserting circularly-permutated GFP into a SWEET transporter\, resulting in a chimera that translate substrate-triggered conformational rearrangements during the transport cycle into detectable changes in fluorescence intensity. We demonstrate that a combination of cell sorting and bioinformatics can be applied as a general approach to accelerate the design of biosensors for in vivo biochemistry. \nFinally\, mass action kinetics analysis of the sensor’s response suggests that SWEETs are low-affinity\, near-symmetric transporters that can rapidly equilibrate intra- and extracellular concentrations of sugars. These types of models provide new insight into the working of sugar transporters and can help realize multiscale\, dynamic simulations of metabolite allocation to guide crop improvement.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-spying-on-sugar-transporters-kinetic-studies-of-biomolecular-sensors/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220302T163000
DTEND;TZID=America/New_York:20220302T163000
DTSTAMP:20260406T070932
CREATED:20220211T021334Z
LAST-MODIFIED:20220211T021334Z
UID:10007081-1646238600-1646238600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Theoretical Foundations of Pre-trained Models"
DESCRIPTION:A pre-trained model refers to any model trained on broad data at scale and can be adapted (e.g.\, fine-tuned) to a wide range of downstream tasks. The rise of pre-trained models (e.g.\, BERT\, GPT-3\, CLIP\, Codex\, MAE) transforms applications in various domains and aligns with how humans learn. Humans and animals first establish their concepts or impressions from different data domains and data modalities. The learned concepts then help them learn specific tasks with minimal external instructions. Accordingly\, we argue that a pre-trained model follows a similar procedure through the lens of deep representation learning. 1) Learn a data representation that filters out irrelevant information from the training tasks; 2) Transfer the data representation to downstream tasks with few labeled samples and simple models.\nThis talk establishes some theoretical understanding for pre-trained models under different settings\, ranging from supervised pretraining\, meta-learning\, and self-supervised learning to domain adaptation or domain generalization. I will discuss the sufficient (and sometimes necessary) conditions for pre-trained models to work based on the statistical relation between training and downstream tasks. The theoretical analyses partly answer how they work\, when they fail\, guide technical decisions for future work\, and inspire new methods in pre-trained models.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-theoretical-foundations-of-pre-trained-models/
LOCATION:Room 307\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220303T110000
DTEND;TZID=America/New_York:20220303T120000
DTSTAMP:20260406T070932
CREATED:20220223T151151Z
LAST-MODIFIED:20220223T151151Z
UID:10007101-1646305200-1646308800@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Learning to Interact With the World: When Generality Meets Precision"
DESCRIPTION:Robotics stands as one of the most impactful and promising endeavors of our times. Learning to interact with the world is fundamental for solving some of our most pressing societal challenges: from taking care of our aging population and aiding with labor-intensive jobs to assisting in climate-related disasters and rescue emergencies. In this talk\, I will argue that such a level of autonomy and performance requires robots that can excel across diverse settings while remaining accurate and reliable. \nMy talk will focus on how we can develop learning algorithms that foster robotic generalization while ensuring the desired task performance. First\, I will present a learning approach to pose estimation for novel objects based on visuo-tactile sensing that doesn’t rely on real data and results in accurate pose distributions. Then\, I will demonstrate how this approach enables precise robotic pick-and-place using task-aware grasping. The robotic system reasons over the models for grasping\, planning\, and perception in order to optimize its actions based only on simulated data. In real experiments\, we demonstrate that our approach learned purely in simulation\, allows robots to successfully manipulate new objects and perform highly accurate placements.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-learning-to-interact-with-the-world-when-generality-meets-precision/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220303T153000
DTEND;TZID=America/New_York:20220303T163000
DTSTAMP:20260406T070932
CREATED:20220211T022112Z
LAST-MODIFIED:20220211T022112Z
UID:10007082-1646321400-1646325000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar:"Privacy and Scalability for Decentralized Cryptographic Systems"
DESCRIPTION:Our existing digital infrastructure requires trust in a small number of centralized entities. The poor fault-tolerance and auditability of this architecture has motivated interest in systems like Ethereum that *decentralize trust across many nodes* by having every node re-execute computations to check their correctness. However\, this strategy leads to poor *privacy* and *scalability* guarantees. \nIn this talk\, I will show how to obtain decentralized trust systems that achieve strong privacy and scalability properties by relying on *efficient cryptographic proofs* (zkSNARKs). In particular\, I will present ZEXE\, a system for *decentralized private computation* where all transactions are indistinguishable from one another\, irrespective of the underlying computation. I will then briefly describe a new paradigm for constructing concretely efficient and easy-to-deploy zkSNARKs.
URL:https://seasevents.nmsdev7.com/event/cis-seminarprivacy-and-scalability-for-decentralized-cryptographic-systems/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220304T103000
DTEND;TZID=America/New_York:20220304T114500
DTSTAMP:20260406T070932
CREATED:20220119T201306Z
LAST-MODIFIED:20220119T201306Z
UID:10007027-1646389800-1646394300@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: Shai Revzen\, University of Michigan\, Ann Arbor\, “Multi-legged slipping is simpler than you think”
DESCRIPTION: Multi-contact sliding mechanics in general and multilegged slipping in particular have long been considered difficult to model.  As a consequence roboticists have avoided building multilegged systems and designing motion plans which include intentional slipping.  I present a series of experiments and mathematical advances that demonstrate how these problems become easier with more contacts.  These advances have allowed us to create fast learning algorithms that identify highly predictive models for the interaction physics of multi-contact gaits from a few dozen cycles of motion.  The consequences are multifold: gait optimization algorithms for slipping and soft robots\, speeding up simulations from linear to logarithmic dependence in the planning horizon\, a deeper understanding of the relationship between Coulomb and Viscous friction\, and perhaps some tantalizing hints as to the evolutionary origins of animals’ motor control. The work presented was funded by the NSF CMMI 1825918\, ARO W911NF-14-1-0573\, ARO W911NF-17-1-0306\, and the D. Dan and Betty Kahn Michigan-Israel Partnership for Research and Education Autonomous Systems Mega-Project.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-multi-legged-slipping-is-simpler-than-you-think/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220304T140000
DTEND;TZID=America/New_York:20220304T150000
DTSTAMP:20260406T070932
CREATED:20220224T134910Z
LAST-MODIFIED:20220224T134910Z
UID:10007102-1646402400-1646406000@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium: "Mechanics of Polymeric Gels"
DESCRIPTION:This talk discusses recent and ongoing research on the multiphysics response of polymeric gels. A polymeric gel is a polymeric material swollen by a fluid\, and the intake or out-flow causes large deformations. Also\, many gels respond to environmental stimuli such as temperature\, electric and magnetic fields\, pH\, and more. The responsiveness of polymeric gels to environmental stimuli has been widely employed in soft robotics\, and the poten-tial applications of soft robots are vast. The fast emerging development of gel-based soft robots makes understanding the mechanics of this class of material an important task for simulating their operation. \n\nThe talk begins with recent experimental observations on the mechanical behavior of polymeric gels. Then a continuum level model for the coupled deformation-diffusion re- sponse of gels that incorporates anisotropy and inelasticity is summarized. That is followed by model calibration and attempts for validation on relatively simple gels. Numerical sim-ulations are performed to show the behavior of the model\, and qualitative comparisons are made to experiments of a soft robotic gripper. Results show that the behavior of polymeric gels is even more dependent on fluid uptake than previously thought.
URL:https://seasevents.nmsdev7.com/event/pics-colloquium-mechanics-of-polymeric-gels/
LOCATION:PICS Conference Room 534 – A Wing \, 5th Floor\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220307T120000
DTEND;TZID=America/New_York:20220307T130000
DTSTAMP:20260406T070932
CREATED:20220207T143311Z
LAST-MODIFIED:20220207T143311Z
UID:10007067-1646654400-1646658000@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: “Smart Immune Receptor Sequencing in Single Cells" (Michael Malone)
DESCRIPTION:Physical Sciences in Oncology Center PSOC@Penn \nSpring 2022 Hybrid-Seminar Series \nTowne 225 / Raisler Lounge @ Noon (EST) \nFor Zoom link \, please contact manu@seas.upenn.edu
URL:https://seasevents.nmsdev7.com/event/psocpenn-seminar-smart-immune-receptor-sequencing-in-single-cells-michael-malone/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Doctoral,Graduate,Student
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220308T110000
DTEND;TZID=America/New_York:20220308T120000
DTSTAMP:20260406T070932
CREATED:20220302T133953Z
LAST-MODIFIED:20220302T133953Z
UID:10007109-1646737200-1646740800@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Dynamics and Control of Quantum Systems"
DESCRIPTION:In practice\, quantum systems of interest are never isolated. The presence of noise or the interaction with an environment can radically change a system’s dynamics\, typically destroying resources such as quantum coherence and entanglement – that is\, destroying the resources that are necessary to benefit from quantum phenomena in applications of quantum science. \nI will present a general framework to study the dynamics of realistic quantum systems from first principles. More specifically\, I will show bounds on the speed with which open-quantum and classical-stochastic systems evolve. In certain regimes\, these bounds correctly capture dynamics in a range of fields\, from quantum and classical thermodynamics to evolutionary biology. \nIn the last part of the talk\, I will introduce a mechanism to control the dynamics of open quantum systems by exploiting measurement feedback from continuous monitoring. I will show how this can\, in turn\, be used to mitigate the effects of the interaction with an environment.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-dynamics-and-control-of-quantum-systems/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220310T110000
DTEND;TZID=America/New_York:20220310T120000
DTSTAMP:20260406T070932
CREATED:20220301T175806Z
LAST-MODIFIED:20220301T175806Z
UID:10007107-1646910000-1646913600@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Quantum Device Benchmarking from Many-Body Quantum Chaos"
DESCRIPTION:Recently\, there has been remarkable progress towards the development of large-scale quantum devices through advances in quantum science and technology. This progress opens new doors for proof-of-principle demonstrations of quantum simulations as well as practically useful applications\, such as quantum-enhanced metrology. However\, these applications require first quantifying how well a quantum device produces a desired target state\, which is currently experimental challenging as existing methods for the quantitative verification of a quantum device require fine-tuned control and substantial experimental resources. In this talk\, I will present a simple and efficient benchmarking protocol to estimate the fidelity of large-scale quantum devices. Our protocol relies only on time evolution of a quantum system undergoing Hamiltonian dynamics\, followed by simple measurements without any sophisticated control and readout. Fundamentally\, this simplification stems from a universal phenomenon associated with many-body chaos from generic\, strongly interacting quantum systems. We demonstrate our benchmarking protocol experimentally for an analog quantum simulator based on a Rydberg atom array\, and numerically for other quantum platforms such as superconducting qubits\, trapped ions\, and itinerant particles in optical lattices.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-quantum-device-benchmarking-from-many-body-quantum-chaos/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220310T153000
DTEND;TZID=America/New_York:20220310T163000
DTSTAMP:20260406T070932
CREATED:20220131T152543Z
LAST-MODIFIED:20220131T152543Z
UID:10007054-1646926200-1646929800@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "The Interface between man and machine | Neural Interfacing for Sensory Feedback and Neuroprosthetic control" (Shriya Srinivasan)
DESCRIPTION:This seminar will be held live and broadcast on zoom – check email for zoom link or contact ksas@seas.upenn.edu. \nDespite immense technological and scientific advancements in prosthetic technologies\, patients rarely use advanced prosthetic devices\, as communicating to these devices is cumbersome and frustrating.  This talk will elucidate new strategies in reconstructive surgical design and neural interfacing that enable amputees to better communicate prostheses as well as receive proprioceptive and cutaneous sensory feedback\, by carefully rewiring mechanoreceptors in the peripheral limbs. Through preclinical and clinical validation\, these interfaces demonstrate restored afferent feedback in the peripheral and central nervous systems\, improved phantom limb sensations\, decreased phantom limb pain and enhanced motor control. Beyond the peripheral limbs\, this talk will explore the neural interfacing of gastric mechanoreceptors through ingestible electronics. These approaches give way to a new design framework that can optimize and eventually dissolve the interface between man and machine.
URL:https://seasevents.nmsdev7.com/event/be-seminar-the-interface-between-man-and-machine-neural-interfacing-for-sensory-feedback-and-neuroprosthetic-control-shriya-srinivasan/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Postdoctoral
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220314T120000
DTEND;TZID=America/New_York:20220314T130000
DTSTAMP:20260406T070932
CREATED:20220207T143502Z
LAST-MODIFIED:20220207T143502Z
UID:10007068-1647259200-1647262800@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: Christina Hueschen
DESCRIPTION:Physical Sciences in Oncology Center PSOC@Penn \nSpring 2022 Hybrid-Seminar Series \nTowne 225 / Raisler Lounge @ Noon (EST) \nFor Zoom link \, please contact manu@seas.upenn.edu
URL:https://seasevents.nmsdev7.com/event/psocpenn-seminar-christina-hueschen/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Postdoctoral
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220314T140000
DTEND;TZID=America/New_York:20220314T160000
DTSTAMP:20260406T070932
CREATED:20220309T192949Z
LAST-MODIFIED:20220309T192949Z
UID:10007115-1647266400-1647273600@seasevents.nmsdev7.com
SUMMARY:CBE PhD Dissertation Defense | "Surface Modification of Solid Oxide Cell Electrodes to Improve the Electrochemical Performance"
DESCRIPTION:Abstract: \n“Solid Oxide Fuel Cells are high temperature\, solid-state\, electrochemical devices that can convert fuels into electricity or produce fuels from excess electricity. Oxygen is reduced at the cathode to oxygen ions which move through the ceramic to the anode. These oxygen ions are used to oxidize fuels at the anode compartment\, producing heat and electrons that will move through an external circuit to produce power.\nAt the cathode the sluggish oxygen reduction kinetics impede the performance of the electrode. A common approach to enhance the cathode performance is infiltration. Often the performance of a cathode is enhanced after the addition of a variety of metal-oxide materials. The common claim is that the infiltrated materials enhance catalytic activity or conductivity. With infiltration however\, it is impossible to control for changes in surface area or conductivity. Atomic Layer Deposition (ALD) was employed to change the surface chemistry of the electrode\, without changing the conductivity\, or surface area of the electrode.\nPerovskite anodes are of interest due to their resistance to many of the issues that plague Ni-cermet (ceramic metal) anode. Their catalytic activity is often lacking\, and as such a variety of methods are employed to enhance this. The most efficient approach is surface modification which allows for increases in activity with minimal metal loadings. ALD was employed to deposit highly disperse oxidation catalysts in order to minimize the metal loadings while maximizing performance. \n\nAt the Ni-cermet anode\, undesirable reactions\, such as carbon fiber formation and Ni oxidation to NiO\, limit the lifetime of the electrode. Surface modification approaches are often employed to protect the Ni surface against these processes. We investigated the use of CeO2 ALD to overcome these challenges. \n\nPerovskites with exclusively 2 + cations (Ba and Sr) in the A-site and Fe in the B-site have recently exhibited great performance as SOFC anodes. The reasoning behind the high catalytic activity of these anodes has not been thoroughly studied. To elucidate the origin of the high activity of these anodes\, the performance and thermodynamics of Ba0.5Sr0.5FeO3 (BSF) anodes was investigated.”
URL:https://seasevents.nmsdev7.com/event/cbe-phd-dissertation-defense-surface-modification-of-solid-oxide-cell-electrodes-to-improve-the-electrochemical-performance/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
END:VCALENDAR