PICS Seminar: "Shock-induced turbulent mixing and interactions with flexible panels through simulations"
2020-10-30 14:00 - 15:00 (America/New_York) | Zoom – Email CIS for link, cherylh@cis.upenn.edu
Two fundamental challenges that arise in the development of air-breathing supersonic combustion ramjet engines (scramjets) for hypersonic flight are: 1) the rapid mixing of fuel and oxidizer that must occur prior to combustion, and 2) the coupling between the engine structure and the flow dynamics. Interactions of shock waves and turbulence that characterize the flow inside scramjets play a key role in both mixing enhancement and aerostructural coupling. We present ongoing efforts on the high-fidelity numerical simulation of these two phenomena.
Scalar mixing under canonical shock-turbulence interactions will be addressed first by means of Direct Numerical Simulation, evaluating the effects of variations in the relevant physical parameters: shock and turbulence Mach numbers, Reynolds number, and Schmidt numbers. The analysis will highlight changes along the shock-normal direction of scalar variance and dissipation-rate budgets, flow topology, and alignments of the scalar gradient with vorticity and strain-rate eigendirections.
Then, we will focus on interactions of shock waves reflecting off turbulent boundary layers that develop along the walls of the scramjet. Rigid and flexible walls will be considered, by coupling a wall-modeled large-eddy simulation solver for the fluid flow with an elastic solid structural solver that accounts for geometric nonlinearities. We will emphasize strong shock/boundary-layer interactions resulting in mean flow separation and low-frequency unsteadiness that can interact with natural frequencies of the structure.

PSOC Webinar: Emily Hatch
2020-11-02 12:00 - 13:00 | PA
Talk title TBC
Physical Sciences in Oncology Center PSOC@Penn
Fall 2020 Webinar Series Mondays @ Noon (EST)
For webinar links, please contact manu@seas.upenn.edu

MEAM/GRASP Seminar: "Saltatorial Locomotion on Terrain Obstacles"
2020-11-03 10:30 - 12:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Robots often struggle to move through complicated environments from cluttered living spaces to treetop canopies where humans and animals flit with ease. Jumping is an exciting locomotion mode that can enable small ground-based robots to maneuver around large obstacles and gaps in complicated environments. A high-power jumping robot can rapidly traverse obstacles, but the resulting fast and forceful stance phases are challenging for control and estimation. In this talk, I will present my work developing a small monopedal jumping robot, Salto-1P: Saltatorial Locomotion on Terrain Obstacles. Salto-1P achieved superlative jumping performance and demonstrated the first robotic wall jump, extreme-acceleration hopping, precise control to traverse obstacles much larger than the robot’s size, and onboard estimation and control to operate outdoors and execute balanced landings.

PICS Alumni Spotlight: "Zahera Jabeen"
2020-11-04 12:00 - 13:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
The PICS Alumni Spotlight is an opportunity for current students to talk and network with alumni. These talks begin with the speaker discussing their education and career paths and then answering questions from students.

CBE Seminar: "Delineating Mechanisms of BMP-mediated Patterning and Organization During Development Through Integrative Experiment and Simulation"
2020-11-04 15:00 - 16:00 | Zoom – Email CBE for link
Abstract

The emergence of coordinated cellular, tissue, and organismal responses rely on complex biological networks. While the connectivity of the networks is increasingly defined, understanding the dynamics of the system and the emergence of coordinated responses at multiple spatial and temporal scales is an unsolved problem in many systems. This is a challenge addressed by all living systems that utilize highly conserved chemical reaction networks that coordinate single cell behavior into tissues and into organisms. To study the coordination, we rely on the back and forth between simulation and experiments. Specifically, we developed and applied integrative simulations reaction-advection-diffusion partial differential equation models to discern the mechanism of Bone Morphogenetic Protein (BMP) signaling along the dorsal/ventral (DV) axis in zebrafish embryos, and in the mouse developing organ or Corti. In each of these systems, gradients of BMP signaling form through the interplay of BMP ligands interacting with other secreted factors that shape the gradient. We developed methods to quantify inputs and outputs of BMP signaling activity, developed AI tools to segment every cell in a developing embryo, and used the data to build and test mathematical models of different biological hypotheses of gradient formation and differentiation. In zebrafish embryonic development, we found that a source-sink mechanism is most consistent with formation of the ventral-to-dorsal gradient of BMP signaling; and in the developing organ of Corti in mouse, we found that the BMP gradient forms an information-maximizing linear profile sufficient for multiple boundary specification along the developing organ. These systems highlight how the back and forth between experiment and simulation drives an integrative understanding of developmental systems.

MSE Seminar: "From Atom to System: Advanced Characterization for Next Generation Energy Storage Materials"
2020-11-05 10:45 - 11:45 | PA
Seminar details forthcoming.

ESE Seminar: "Accelerating MRI with Deep Learning"
2020-11-06 12:00 - 13:00 | Zoom – Email ESE for Link jbatter@seas.upenn.edu
Magnetic Resonance Imaging (MRI) can be accelerated by sampling below the Shannon-Nyquist rate via compressed sensing techniques. In this talk, I will consider the problem of optimizing the under-sampling pattern in a data-driven fashion, which has been an open problem for over a decade. For a given sparsity constraint, our method optimizes the under-sampling pattern and reconstruction model, using a computationally efficient end-to-end deep-learning strategy. We call our method Learning-based Optimization of the Under-sampling PattErn, or LOUPE. Our experiments with brain and knee MRI scans show that the LOUPE-derived pattern can yield significantly more accurate reconstructions compared to standard under-sampling schemes. I will also present results for prospectively collected in-vivo images that demonstrate the practical utility of LOUPE in speeding up MRI scans.

SIG Seminar:"Computational Design for the Next Manufacturing Revolution"
2020-11-06 13:00 - 14:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
Abstract: 3D printers are radically transforming the aerospace and automotive industries. Whole-garment knitting machines allow the automated production of complex apparel and shoes. Manufacturing electronics on flexible substrates enable a new range of integrated products for consumer electronics and medical diagnostics. These advances demonstrate the potential for a new economy of on-demand production of objects of unprecedented complexity and functionality. In my talk, I argue that the field of computational design is essential for the next revolution in manufacturing. To build increasingly functional, complex and integrated products, we need to create design tools that allow their users to efficiently explore high-dimensional design spaces by optimizing over a set of performance objectives that can be measured only by expensive computations.

PICS: "Python Workshop"
2020-11-07 10:00 - 16:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
The Penn Institute for Computational Science (PICS) will be hosting a Python workshop on Saturday, November 7 from 10:00am – 3:30pm via Zoom. This course is designed to be an introduction to programming in Python. In this workshop you will learn to write clean, readable, and fast Python code with a focus on graphics-based programming.
In order to attend please click here and RSVP. The workshop will be capped at 30 people. Students enrolled in the PICS Certificate program will have priority enrollment.

Doctoral Dissertation: "Iron Imaging in Myocardial Infarction Reperfusion Injury" (Brianna Moon)
2020-11-09 11:30 - 12:30 | PA
The Department of Bioengineering at the University of Pennsylvania and Dr. Walter Witschey are pleased to announce the Doctoral Dissertation Defense of Brianna Moon. The Defense will take place via Zoom. Contact moonbri@seas.upenn.edu for the link and passcode.

Title: Iron Imaging in Myocardial Infarction Reperfusion Injury
Date: November 9th, 2020
Time: 11:30am EST

PSOC Webinar: “Chromatin motion and DNA repair” (Pierre-Alexandre Vidi)
2020-11-09 12:00 - 13:00 | PA
“Chromatin motion and DNA repair”
Physical Sciences in Oncology Center PSOC@Penn
Fall 2020 Webinar Series Mondays @ Noon (EST)
For webinar links, please contact manu@seas.upenn.edu

CBE PhD Dissertation Defense | Polymer Mechanics and Dynamics in Polymer Nanoparticle Composites
2020-11-09 13:00 - 15:00 | Zoom – Email CBE for link
Abstract:
“Polymer nanoparticle composites (PNCs) have become an important topic of research due to their highly tunable macroscopic properties. Compared to the pure polymers, PNCs exhibit increase in mechanical strength, altered thermodynamic properties, and simultaneous improvement in permeability and selectivity in small molecule transport. Understanding the fundamental physics that control the behavior of both components in the PNCs can provide insights to the material design. In PNCs, the microscopic variations often dominate the behavior at the macroscopic level. Previous research has shown significant deviations in both polymer conformation and dynamics near the nanoparticle (NP) surfaces from bulk polymers. However, the heterogeneous nature of the PNCs makes understanding microscopic details using macroscopic experiments a difficult task. Therefore, computational methods have been employed to investigate the polymer conformation, mechanics, and dynamics at the molecular level. In this dissertation, I use PNCs with two levels of NP loading to investigate the origins of the various changes in properties. First, I use molecular dynamics (MD) simulations to examine a class of PNCs with ultra-high NP loading, in which the volume fraction of NPs is near the random-close-pack limit ( >50% ). This class of PNCs can be produced with either partial or complete filling of polymers. In these PNCs, the polymer chains are highly confined due to the large number of NP surfaces, thus are drastically altered in their conformation and dynamics. The second PNC system studied in this dissertation has a dilute amount of well-dispersed NPs to avoid NP-NP interaction and polymer confinement. In this case, I use both MD simulations and classical density functional theory (cDFT) for fluids to understand the role of NP-polymer interactions, solid curvature, and polymer molecular weight.”

MEAM Seminar: "Merging Human-Machine Intelligence with Soft Materials Technology"
2020-11-10 10:30 - 12:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Whereas human tissues and organs are mostly soft, wet and bioactive; machines are commonly hard, dry and biologically inert. Merging humans, machines and their intelligence is of imminent importance in addressing grand societal challenges in health, sustainability, security, education and joy of living. However, interfacing humans and machines is extremely challenging due to their fundamentally contradictory properties. At MIT Zhao Lab, we exploit soft materials technology to form long-term, high-efficacy, multi-modal interfaces and convergence between humans and machines. In this talk, I will first discuss the mechanics and general principles to design extreme properties including tough, resilient, adhesive, strong, fatigue-resistant and conductive for soft materials. Then I will discuss a set of soft materials technology platforms, including i). bioadhesives for instant strong adhesion of diverse wet dynamic tissues and machines; ii). bioelectronics for long-term multi-modal neural interfaces; iii). biorobots for teleoperated and autonomous navigations and operations in previously inaccessible lesions such as in cerebral and coronary arteries. I will conclude the talk with a perspective on future human-machine convergence enabled by soft materials technology.

ESE Grace Hopper Lecture: "Scalable Photonics: An Optimized Approach"
2020-11-10 12:00 - 13:00 | Zoom – Email ESE for Link jbatter@seas.upenn.edu
Classical and quantum photonics with superior properties can be implemented in a variety of old (silicon, silicon nitride) and new (silicon carbide, diamond) photonic materials by combining state of the art optimization and machine learning techniques (photonics inverse design) with new fabrication approaches. In addition to making photonics more robust to errors in fabrication and temperature, more compact, and more efficient, this approach is also crucial for enabling new photonics applications, such as on-chip laser-driven particle accelerators, and semiconductor quantum simulators.

CIS Seminar:"Critical Computing Education
2020-11-10 15:00 - 16:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
Computing can be a wondrous, powerful tool, bringing us information, experiences, and connections that transform our lives for the better. However, as many of us have learned, computing has also contributed to great injustices, increasing surveillance of our most vulnerable populations, eroding the middle class through economic displacement, and amplifying historical injustices embedded in society. In this talk, I discuss our responsibility as scholars to engage both the powers and perils of computing in our research, teaching, and service. I specifically focus on three sources of injustice that are missing from computing literacy: the limits of computing, the limits of data, and the responsibility of computing professionals to center these limits in their work. Throughout, I highlight recent discoveries from my lab as examples for how to engage these topics through research, and end with ideas for how the audience can engage in their own research, teaching, and service.

CIS Seminar:"Critical Computing Education"
2020-11-10 15:00 - 16:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu

Doctoral Dissertation Defense: "Light-inducible control of microtubule organization in minimal cell-like compartments" (Jessica Bermudez)
2020-11-11 12:30 - 14:30 | PA
The Department of Bioengineering at the University of Pennsylvania and Dr. Matthew Good are pleased to announce the Doctoral Dissertation Defense of Jessica Bermudez. The public is welcome to attend the Zoom meeting via the details below.

Title: Light-inducible control of microtubule organization in minimal cell-like compartments
Date: Wednesday, November 11th, 2020
Time: 12:30 PM EST

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CBE Seminar: "The Role of Utilization in Meeting Mid-Century Carbon Removal Targets"
2020-11-11 15:00 - 16:00 | Zoom – Email CBE for link
Abstract
The utilization of CO2 broadly applies to any process that transforms captured CO2 into valuable products. These processes strive to achieve any of the following objectives: (1) permanent storage (2) revenue generation and/or (3) avoiding emissions of conventional products with high amounts of embodied carbon. This talk will explore how carbon utilization can be leveraged to help us meet the ambitious gigatonne-scale removal targets proposed by many agencies as necessary to combat climate change by mid-century. Topics covered will include the importance of CO2 source, temporal aspects of storage, the role of stock vs flux, scaling limitations, economic potential and risk. The significance and mutual dependency of these factors will be illustrated in regional merit-order modeling, as well as select case studies on lifecycle emission assessments. These results inform policymakers, investors and scientists on both the strengths and shortcomings of CCUS as a climate mitigation strategy.

MSE Seminar: "Nano-Volumetric Materials Properties of Ferroelectrics and Photovoltaics via Tomographic AFM"
2020-11-12 10:45 - 11:45 | PA
Nano- and meso- scale materials properties are crucial to the macroscopic performance of a wide range of functional and photovoltaic devices. In 2-dimensions, photoconductivity, ferroelectricity, and even domain dynamics have thus been investigated for decades now especially using variations of Atomic Force Microscopy. Our work and others reveals how these properties are frequently mediated by strain, orientation, grain boundaries, and other microstructural defects or heterogeneities. However, practical devices are often sensitive to, or even controlled by, sub-surface effects or thickness dependencies related to microstructure and concentration, polarization, and/or field gradients. Therefore, we are advancing Tomographic AFM for volumetric materials property mapping, with voxels of properties on the order of ~10 nm3. With polycrystalline photovoltaics such as MAPbI3 and CdTe, TAFM literally uncovers new pathways to improve carrier separation via inter- and intra- granular defects (Luria, Nature Energy, 2017; Song, Nature Communications, 2020). For BiFeO3, Tomographic AFM confirms Kay-Dunn thickness scaling, LGD behavior with a minimum switchable thickness of <5 nm, and even co-located domain and current maps which together directly reveal sub-surface topological defects (Steffes, PNAS, 2018). Such volumetric insight is increasingly important for engineering optimal performance and reliability of real-world, 3-Dimensional materials devices.

MEAM Seminar: "How to Make Your Ocean Smarter"
2020-11-12 13:30 - 14:30 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Our oceans drive worldwide weather-climate systems; our rivers serve as nutrient conduits; and our marine ecosystems house the largest repository of biodiversity and mineral resources on the planet. Humans have relied on rivers, lakes, and oceans for transportation, energy generation, farming, and recreation throughout our history. And today, robots are critical tools in our stewardship of these resources. However, there are significant autonomy challenges when working in dynamic and uncertain environments like oceans and rivers. Robot dynamics are tightly coupled to those of the environment, while communication and localization are limited.
Control under these conditions can be exacting, but environmental dynamics may be harnessed to plan energy efficient paths and to maintain network connectivity. Networked robot teams can collect data to construct high fidelity models of the environmental dynamics which can be integrated into robot control and planning. Those same models can be used to guide robot control and sampling strategies to increase their predictive power. In this talk, I will present our vision of a smart ocean observational framework to improve forecasting of weather-climate systems, mitigation of contaminant dispersions, and coordination of maritime search and rescue and humanitarian efforts.

CIS Grace Hopper Distinguished Lecture:"Video Data Management: From Data Models to Data Storage and Benchmarking."
2020-11-12 15:00 - 16:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
The proliferation of inexpensive high-quality cameras coupled with recent advances in machine learning and computer vision have enabled new applications on video data. This in turn has renewed interest in video data management systems. In this talk, we explore several challenges related to video data management. We start by discussing data models. How should we expose video data to make it queryable by applications? We look in particular at the case of 360-degree videos. Second, we explore components of video data storage. How can we store videos in a way that makes them efficiently queryable? Finally, we discuss the problem of benchmarking video data management systems.

SIG Seminar:"From Bits to Bricks – Bridging Building Energy Modeling and Simulation with Graphics"
2020-11-13 10:00 - 11:00 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
Computer graphics is often used to visualize complex imagery for the
film and game industries, however, computer graphics can also be used
to solve a diverse set of transdisciplinary problems. In this talk, I
will introduce research that bridges building energy modeling and
simulation and computer graphics. Buildings are a leading contributor
to total energy consumption in the United States –responsible for
over 48 percent of the total energy use in our country. Architecture,
engineering, and construction (AEC) is currently a 10 trillion dollar
industry and one of the top consumers of raw materials. I’ll talk
about our recent projects that focus on modeling and simulating
responsive architecture and approaches to retrofitting through
numerical modeling and simulation to provide collaboration tools to
the design process. I will introduce our first principle physics-based
approach to energy and light simulation that produces more informed
design choices to architects and engineers and show how computer
graphics has been formalized to conduct basic research in building
science. The design, analysis, and construction of sustainable
buildings require an unprecedented degree of technical sophistication
that demands a new transdisciplinary synthesis of engineering,
architecture, and social science.

MEAM Ph.D. Thesis Defense: “All-Passive Hardware Architectures for Neuromorphic Computation”
2020-11-13 15:00 - 16:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Human brains demonstrate how simple computational primitives can be combined in massively parallel ways to produce networks capable of identifying complicated patterns in sensory data. In contrast, electronic computers adopt hardware architectures that process information serially, leading to higher latency and power consumption when implementing intrinsically parallel algorithms, such as neural networks. This software-hardware architectural mismatch has acquired greater attention due to the widespread adoption of large neural networks and has encouraged the prospect of specialized neuromorphic computers. There is great interest in low latency analog neuromorphic designs that utilize passive crossbar arrays to accomplish the dual tasks of storing synaptic weights and computing dot products. Although this compute-in-memory paradigm promises high circuit density and 3D integrability, prevalent implementations combine them with crossbar-incompatible CMOS neurons, a paring that impedes overall system scalability. This thesis addresses the scalability bottleneck by evolving fully crossbar – compatible neuromorphic architectures based on passive circuit embodiments of neuron and synapses.
We demonstrate via SPICE circuit simulations how a shallow network of diode-resistor based passive neurons and resistive voltage summers, despite its inherent inability to buffer, amplify and invert signals, can recognize MNIST digits with 95.4% accuracy. We introduce weight-to-conductance mappings that enable resource-efficient implementation of negative weights. The performance impacts of nanoscale defects are evaluated and methods to boost fault-tolerance are proposed. Compared with conventional implementations, we find all-passive neuromorphic hardware promise higher speed, smaller footprints, and improved vertical scalability.

PSOC Webinar: “Visualizing Cancer Biology: From Single Molecules to Systems" (Xiolin Nan)
2020-11-16 12:00 - 13:00 | PA
“Visualizing Cancer Biology: From Single Molecules to Systems”
Physical Sciences in Oncology Center PSOC@Penn
Fall 2020 Webinar Series Mondays @ Noon (EST)
For webinar links, please contact manu@seas.upenn.edu

MEAM Seminar: "Bilevel Optimization for Control, Learning, and Multi-contact Robotics"
2020-11-17 10:30 - 12:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Whether operating in a manufacturing plant or assisting within the home, many robotic tasks requires safe and controlled interaction with a complex and changing world. In this talk, I will present our recent progress on learning and control in contact rich settings. In the first segment, I will show how integrating the non-smooth structure of contact dynamics into a learning framework can dramatically improve accuracy and data efficiency when identifying or learning frictional dynamics. Our approach leads to a well-conditioned bilevel optimization problem, avoiding the numerical stiffness and inaccuracies that plague traditional approaches. In the second part of this talk, I will focus on the role of simple, low-dimensional models used in real-time planning for walking robots. Hand-engineered models, typically based in inverted pendulums, are widely used but lead to fundamental limitations on performance. Our recent work, leveraging trajectory optimization within bilevel optimization, to automatically synthesize simple models designed to succeed across a space of tasks. Time-permitting, I will also discuss our work on using bilinear matrix inequalities to leverage tactile feedback within provably stable control policies.

ESE Seminar: "A New Era of Open-Source System-on-Chip Design"
2020-11-17 11:00 - 12:00 | Zoom – Email ESE for Link jbatter@seas.upenn.edu
Open-source software has been a critical enabler for tremendous innovation in the software ecosystem over the past two decades. Inspired by this success, open-source hardware involves making the high-level description of hardware components freely available for others to study, change, distribute, and ultimately use in fabricating their own hardware components. Unfortunately, open-source hardware has had a relatively bleak history and has yet to offer the same kind of transformative impact in the hardware ecosystem. At the same time, emerging applications in visual computing, data science, and machine learning are demanding more performance with less resources motivating an increasing need for accelerator-centric system-on-chip (SoC) design. We need hardware startups to drive the next phase of software/hardware innovation, and hardware startups need open-source hardware.
In this talk, I will briefly discuss some recent trends in open-source electronic design automation, instruction set design, and component development that suggest we may be entering a new era of open-source SoC design. I will then describe two projects in my own research group that concretely illustrate these trends. In the first part of the talk, I will discuss PyMTL, a new framework which leverages Python to create a domain-specific embedded language for hardware modeling, generation, simulation, and verification. PyMTL has the potential to improve the productivity and quality of open-source hardware design. In the second part of this talk, I will discuss the Celerity SoC, a 5x5mm 385M-transistor chip in TSMC 16nm designed and implemented by a team of students and faculty from UC San Diego, University of Michigan, and Cornell as part of the DARPA CRAFT program. The chip went from PDK access to tapeout in just nine months largely owing to extensive use of open-source hardware. My talk concludes with a call-to-action for the academic community to make open-source hardware a centerpiece of their activities. Academics have a practical and ethical motivation for using, developing, and promoting open-source electronic design automation tools and open-source hardware designs. We should be leaders in this new era of open-source system-on-chip design.

Immunology/BE Seminar: “Engineering Next-Generation CAR-T Cells for Cancer Immunotherapy” (Yvonne Chen)
2020-11-17 16:00 - 17:00 | PA
This event is part of the Penn Institute for Immunology Colloquium seminar series and is co-hosted by the Department of Bioengineering. This virtual event will be held on Bluejeans.
Attend the live seminar via this link. Or download the Bluejeans app and and enter ID: wxbzgity
Contact ifiadmin@pennmedicine.upenn.edu with any questions.
The adoptive transfer of T cells expressing chimeric antigen receptors (CARs) has demonstrated clinical efficacy in the treatment of advanced cancers, with anti-CD19 CAR-T cells achieving up to 90% complete remission among patients with relapsed B-cell malignancies. However, challenges such as antigen escape and immunosuppression limit the long-term efficacy of adoptive T-cell therapy. Here, I will discuss the development of next-generation T cells that can target multiple cancer antigens and resist immunosuppression, thereby increasing the robustness of therapeutic T cells against tumor defense mechanisms. Specifically, I will discuss the development of multi-input receptors and T cells that can interrogate intracellular antigens. I will also discuss the engineering of T cells that can effectively convert TGF-beta from a potent immunosuppressive cytokine into a T-cell stimulant. This presentation will highlight the potential of synthetic biology in generating novel mammalian cell systems with multifunctional outputs for therapeutic applications.

Neuroengineering/BE Seminar: “Photovoltaic Restoration of Sight in Age-related Macular Degeneration” (Daniel Palanker)
2020-11-18 13:00 - 14:00 | PA
Presented by The Center for Neuroengineering and Therapeutics Presents and The Bioengineering Department.
Check email for zoom link or Everett Prince at eprince@seas.upenn.edu.
Retinal degenerative diseases lead to blindness due to loss of the “image capturing” photoreceptors, while neurons in the “image-processing” inner retinal layers are relatively well preserved. Information can be reintroduced into the visual system using electrical stimulation of the surviving inner retinal neurons. We developed a photovoltaic substitute of photoreceptors which convert light into pulsed electric current, stimulating the secondary retinal neurons. Visual information captured by a
camera is projected onto the retina from augmented-reality glasses using pulsed near-infrared (~880nm) light. This design avoids the use of bulky electronics and wiring, thereby greatly reducing the surgical complexity. Optical activation of the photovoltaic pixels allows scaling the number of electrodes to thousands. In preclinical studies, we found that prosthetic vision with subretinal implants
preserves many features of natural vision, including flicker fusion at high frequencies (>30 Hz), adaptation to static images, antagonistic center-surround organization and non-linear
summation of subunits in receptive fields, providing high spatial resolution. Results of the clinical
trial with our implants (PRIMA, Pixium Vision) having 100μm pixels, as well as preclinical
measurements with 75 and 55μm pixels, confirm that spatial resolution of prosthetic vision can
reach the pixel pitch. Remarkably, central prosthetic vision in AMD patients can be perceived
simultaneously with peripheral natural vision. For broader acceptance of this technology by patients who lost central vision due to agerelated macular degeneration, visual acuity should exceed 20/100, which requires pixels smaller than 25μm. I will describe the fundamental limitations in electro-neural interfaces and 3-dimensional configurations which should enable such a high spatial resolution. Ease of
implantation of these wireless arrays, combined with high resolution opens the door to highly functional restoration of sight.

CBE PhD Dissertation Defense | 3D Porous High Areal Capacity Lithium-ion Micro-Batteries Enabled by Electrochemical Techniques
2020-11-18 15:00 - 17:00 | Zoom – Email CBE for link
Abstract:
This study involves design and fabrication of scalable, high surface area, and porous 3D metal network-based Li-ion micro-batteries with energy and power that meet the demands of commercial microelectronics. A facile high current hydrogen-templated electroplating technique is utilized to generate 3D structures millimeter scale in z-direction through a facile route, which serve as the scaffolds and current collectors for battery electrodes. A solid polymer electrolyte or gel electrolyte was utilized to increase stability and safety of the energy storage device. Areal capacity high as 30 mAh/cm 2 with stable cycling performance has been demonstrated on the half-cell level, which can be attributed to the high surface area and low tortuosity from the porous electrodes.

MSE Seminar: "Interface Engineering in Nanoceramics"
2020-11-19 10:45 | PA
Details forthcoming.
