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        "time_start":"13:30:00",
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        "time_zone":"America\/Detroit",
        "event_title":"CoderSpaces (Mondays)",
        "occurrence_title":"",
        "combined_title":"CoderSpaces (Mondays): Drop-in, Virtual Office Hours",
        "event_subtitle":"Drop-in, Virtual Office Hours",
        "event_type":"Meeting",
        "event_type_id":"14",
        "description":"Are you grappling with a piece of code, trying to compute on a cluster, or just getting started with a new method such as machine learning? Then we might have just the right space for you.\r\n\r\nAll members of the U-M community are invited to join our weekly virtual CoderSpaces, Mondays \u2013 Thursdays, during the Summer 2021 term to get research support and connect with others.\r\n\r\nThe virtual sessions are designed to assist faculty, staff, and students with research methodology, statistics, data science applications, and computational programming for research.\r\n\r\nOur hosts have a wide set of methodological and technological expertise. They come to you from a variety of departments and disciplines and are looking forward to serving the U-M community in their research endeavors.\r\n\r\nCoderSpaces provide a casual, productive, and inclusive environment. Everyone is welcome regardless of skill level.\r\n\r\nMondays 1:30-3 p.m.\r\n\r\nJoin via Zoom* (https:\/\/umich.zoom.us\/j\/97155787515)\r\n*Users will have to sign in with their UMICH (Level-1) credentials.\r\n\r\nwith Andrew Hlynka (CSCAR), Charles Antonelli (LSA Tech), Jonathan Golob (Michigan Medicine)\r\n\r\nExpertise: 3D graphical applications, C, C++, C#, CMake\/GNU Make, Fortran, Git, high performance computing, Java, JavaScript, Julia, Matlab, mobile app development, MPI, OpenMP, parallelization, performance analysis, PBS, Python, R, reproducible workflows (nextflow), shell, Slurm, SQL, statistical modeling",
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        "event_title":"BME PhD Defense: Ahmet Emre",
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        "combined_title":"BME PhD Defense: Ahmet Emre: Bioinspired Nanocomposites for Structural Energy Storage",
        "event_subtitle":"Bioinspired Nanocomposites for Structural Energy Storage",
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        "event_type_id":"16",
        "description":"Energy storage is an integral part of life. Living creatures have developed a distributed and structural energy storage system to survive under various and sometimes extreme conditions. Similarly, energy storage is critical for modern life to power from small biomedical instruments to large aircraft. There are still several challenges against efficient and safe energy storage utilization due to the mechanical, chemical, and physical limitations of existing materials. Inspired by biological structures, we present multifunctional nanocomposites from aramid nanofibers (ANF), a nanoscale version of Kevlar, to address the safety and efficiency of various battery chemistries and enable structural energy storage to increase energy density. High mechanical properties of ANF suppress dendrite formation, and tunability with different copolymers and fabrication methods allow ANF-based nanocomposites to meet specific needs of different battery chemistries.\r\n\r\nIn the first part of this thesis, we engineered biomimetic solid electrolyte from ANF and polyethylene oxide for zinc batteries inspired by the cartilage structure. These strong nanocomposites can block stiff zinc dendrite and prevent short circuits over cycles. Resilience to plastic deformation and damage while having no leaking fluids or cracks is essential for the safety of, for instance, electrical vehicles employing such batteries. These load-bearing batteries can be used as a structural component and increase energy density by simply avoiding inactive parts. As a proof of concept, we utilized this battery on a commercial drone as an auxiliary energy storage unit to extend flight endurance by about 20%.\r\n\r\nThe second part of the thesis addresses a specific polysulfide shuttle problem in lithium-sulfur batteries utilizing bioinspired ANF nanocomposites. Mimicking ion channels on the cell membrane, we engineered biomimetic nanochannels (1nm diameter) for selectively allowing lithium-ion passage while physically blocking lithium polysulfide species (>2nm) on the cathode side. Selective ion transport through nanochannels is also modeled by finite element analysis, COMSOL. These ion channels allow us to reach >3500 cycles.\r\n\r\nIn addition to previous solid and liquid electrolyte systems, here in the last part of the thesis, we present a tunable quasi-solid polymer electrolyte to take advantage of both electrolyte features while minimizing their individual risks and drawbacks. Similar to the kidney filtration system, specifically the glomerular basement membrane, this gel electrolyte filters ions depending on their size and charge. Selective permeability and regulated ion transport provide safe and stable charge\/discharge cycles. High mechanical properties keep functionality under extreme conditions, including high temperature and nail penetration. We integrated pouch cells in various prototypes to show practical utilization of our structural batteries, including health monitoring devices, robotic prosthetics, and electric vehicles.\r\n\r\nTaken together, mimicking structural and functional properties of multifunctional biological materials, i.e., cartilage, we present a novel multifunctional nanocomposite system that can be tailored to the specific needs of numerous structural energy storage applications.\r\n\r\nDate: Monday, August 9, 2021\r\nTime: 2:00 PM\r\nZoom:  https:\/\/umich.zoom.us\/j\/92570283886\r\nChair: Prof. Nicholas Kotov",
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        "event_title":"BME PhD Defense: Steven Cutlip",
        "occurrence_title":"",
        "combined_title":"BME PhD Defense: Steven Cutlip: An Internal Model Principle Approach to Modeling Predictive Human Behavior",
        "event_subtitle":"An Internal Model Principle Approach to Modeling Predictive Human Behavior",
        "event_type":"Presentation",
        "event_type_id":"16",
        "description":"For the sensorimotor system to complete motor tasks it controls the body, it controls objects that the sensorimotor system acts upon within the environment, and it anticipates future states of the environment. The sensorimotor system is known to adapt and improve in performance with practice in response to predictable phenomena. The literature explains motor adaptation and performance improvement in terms of models, called internal models, of future loads. The theory of internal models has been investigated in the neuroscience and human motor behavior communities, where electrophysiological data and motor performance experiments have yielded rich data in support of the role of predictive modeling.\r\n\r\nInternal models can be divided into two types: internal models of the plant and internal models of exogenous processes. While internal models of the plant have a rich history and have been studied extensively, literature on internal models of exogenous processes is less developed. This dissertation introduces the Internal Model Principle (IMP) as a tool for modeling internal models of exogenous processes. This dissertation further extends the usefulness of the IMP for modeling human motor control by extending the model to handle sensorimotor tasks that feature signal blanking.\r\n\r\nHaptic feedback can be considered as an exogenous signal (a disturbance) whose features can be predicted because they are produced by the plant under control. Haptic feedback is an information signal providing the receiver feedback about the state of the system. However, haptic feedback is also a power signal; sufficient force due to haptic feedback can backdrive the biomechanics of a participant. In this dissertation these topics are explored in two studies, one in the context of driving oscillations in a spring-mass system and the other in the context of shared control design for semi-autonomous vehicles.\r\n\r\nDate: Monday, August 9, 2021\r\nTime: 2:00 PM\r\nZoom: https:\/\/umich.zoom.us\/j\/97211413457\r\nChair: Brent Gillespie",
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