Penn Engineering Commencement: Master's Ceremony
2022-05-13 14:00 - 16:30 (America/New_York) | Palestra, 223 South 33rd Street, Philadelphia, PA, 19104, United States
Celebrate the Penn Engineering 2022 Master’s Graduates. Additional information, including speakers and live-stream access is available here.

Penn Engineering Commencement: Undergraduate Ceremony
2022-05-14 14:00 - 16:30 | Palestra, 223 South 33rd Street, Philadelphia, PA, 19104, United States
Celebrate the Penn Engineering Undergraduate Class of 2022. Additional information, including speakers and live-stream access is available here.

ESE Ph.D. Thesis Defense: "Integrated Diamond-based Devices for Quantum Sensing and Communication"
2022-05-18 10:00 - 12:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The nitrogen-vacancy (NV) center in diamond has been integral to the advancement of quantum technologies. It has enabled key demonstrations in quantum networks and distributed quantum computing, as well as impressive proof-of-concept devices in nanoscale, sub-cellular imaging and sensing. The NV center – a point defect in diamond with an optically addressable electron spin – boasts several advantages such as long coherence times and quantum control in ambient conditions. At the same time, the NV center still faces significant engineering challenges in the realization of scalable quantum devices. The high-refractive index of diamond in the visible spectrum results in inefficient photon collection, and the NV center’s sensitivity to charge and spin fluctuations at surfaces and interfaces necessitates deeply embedded NV centers for coherence-limited applications, which further worsens readout efficiency. The challenging optical interface has necessitated the use of high numerical-aperture objectives and free space optics, which are non-ideal components for scalable devices. On the other hand, benchtop frequency synthesizers and sequence generators typically used in laboratory experiments inhibit the packaging of NV centers for deployment outside of laboratory environments. This thesis focuses on the realization of integrated quantum devices using the NV center and targets miniaturization of the host crystal, the optical interface, and quantum control sequence generators. First, it discusses efforts and progress in realizing chemically active quantum sensors based on NV centers embedded in nanodiamonds. Following, it presents the miniaturization of collection optics through the coupling of an immersion metalens fabricated on bulk diamond to a single NV center in the crystal. Finally, it lays out performance considerations for integrated sequence generators to preserve the NV center’s coherence properties, and demonstrates quantum control at room temperature of a NV center using a CMOS control signal generator. To conclude, this thesis discusses future potential for further integrating and miniaturizing diamond-based quantum devices.

PSOC Seminar: "Nanotechnologies for the Research, Detection, and Treatment of Cancer and Allied Diseases" (Daniel Heller)
2022-05-23 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
PSOC seminar (Hybrid) : 12.00-1.00pm (EST)
Send requests for the Zoom link to manu@seas.upenn.edu
Raisler Lounge (Towne 225)

MEAM Seminar: "Aluminum Scandium Nitride Films for Microelectromechanical Systems Resonator’s Next-Generation Cellular Technology"
2022-05-24 10:00 - 11:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Advancements in wireless and sensor technology have resulted in increasing demand for piezoelectric MEMS devices in wireless handsets and base stations, automobile technology, health monitoring sensors, and environmental sensors. Due to its high-quality factor (Q), Young’s modulus, sound velocity, and low mechanical and dielectric losses, AlN is an advantageous resonator material with applications in radio frequency filtering. AlN’s low piezoelectric coefficients, however, limit its application, especially when large electromechanical coupling is required such as wide bandwidth acoustic filters and energy harvesters. In 2009 it was discovered that alloying AlN with Scandium (Sc) increases its d33 piezoelectric coefficient by over 500% and maintains compatibility with post-CMOS integration when deposited below 〖400〗^∘{1}*. As process parameters and Sc levels are modified to enhance performance, this also impacts the built-in stress in the film. Undesired stress can degrade device performance in thin films. Undesired phases and anomalously oriented grains (AOGs) reduce piezoelectric coefficients, film orientation, and modify stress. AOGs also render etching of device structures problematic as the AOG regions etch at a much lower rate.
This presentation will discuss the origins of stress and anomalous grain formation in AlScN physical vapor deposition processes, establish methods to control the stress, and inhibit anomalous grain growth at a range of scandium alloying levels to yield high quality AlScN films with large piezoelectric coefficients. Methods for mitigation and understanding of the physical mechanism behind stress gradients in AlScN thin films to reduce out-of-plane deformations in released MEMS structures will also be discussed. I demonstrate a technique where the total process gas flow is varied during the deposition to compensate for the native through-thickness stress gradient in sputtered AlScN thin films. Finally, I will provide methods extract the AlScN stiffness, piezoelectric, and permittivity tenors from MEMS structures carefully designed to isolate various electromechanical parameters.
{1}*M. Akiyama, T. Kamohara, K. Kano, A. Teshigahara, Y. Takeuchi, and N. Kawahara. (2009). Enhancement of piezoelectric response in scandium aluminum nitride alloy thin films prepared by dual reactive cosputtering. Advanced Materials, 21(5), 593-596.

PSOC Seminar: “Developing integrated single-cell epigenome and transcriptome sequencing technologies to study early mammalian development" (Siddharth Dey)
2022-05-31 12:00 - 13:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
PSOC seminar (Hybrid) : 12.00-1.00pm (EST)
Send requests for the Zoom link to manu@seas.upenn.edu
Wu Chen Auditorium

BE Doctoral Dissertation Defense: "Application of Functional Near-Infrared Spectroscopy to Examine the Neurophysiology of the Injured Adolescent Brain" (Divya Jain)
2022-06-01 15:30 - 17:30 | Room 1120B, Roberts Center for Pediatric Research, 2716 South Street, Philadelphia, PA, 19146, United States
The Department of Bioengineering at the University of Pennsylvania, Dr. Kristy Arbogast and Dr. Catherine McDonald are pleased to announce the Doctoral Dissertation Defense of Divya Jain

Title: Application of Functional Near-Infrared Spectroscopy to Examine the Neurophysiology of the Injured Adolescent Brain
Date: Wednesday, June 1st, 2022
Time: 3:30 PM
Location: Roberts Center for Pediatric Research (2716 South St, Philadelphia, PA 19146), Room 1120B

The public is invited to attend in-person or virtually at the link below:
Zoom Link: https://upenn.zoom.us/j/91632121762?pwd=[REDACTED]
Meeting ID: 916 3212 1762
Password: [REDACTED]

PSOC@Penn Talk: “Lectin-glycan affinity in nanobio theragnostics: The specific capture of pancreatic cancer exosomes and the targeted therapy of tumor cells” (Jonghoon Choi)
2022-06-06 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Contact manu@seas.upenn.edu for the Zoom link.

BE Doctoral Dissertation Defense: "Experimental and computational analyses of locomotor rhythm generation and modulation in Caenorhabditis elegans" (Hongfei Ji)
2022-06-06 13:00 - 15:00 | https://upenn.zoom.us/j/96715197752
The Department of Bioengineering at the University of Pennsylvania and Dr. Chris Fang-Yen are pleased to announce the Doctoral Dissertation Defense of Hongfei Ji.
Title: Experimental and computational analyses of locomotor rhythm generation and modulation in Caenorhabditis elegans
Date: June 6, 2022
Time: 1:00 pm
Zoom link

BE Doctoral Dissertation Defense: "Machine learning as tool and theory for computational neuroscience" (Ari Benjamin)
2022-06-07 15:00 - 17:00 | Goddrd 101
The Department of Bioengineering at the University of Pennsylvania and Dr. Konrad Kording are pleased to announce the Doctoral Dissertation Defense of Ari Benjamin.

Title “Machine learning as tool and theory for computational neuroscience”,
Date: Tuesday, June 7th
Time: 3:00pm
Location: Goddard 101 and in the Zoom room:
https://upenn.zoom.us/j/92613907755?pwd=[REDACTED]

Meeting ID: 926 1390 7755
Passcode: [REDACTED]

The public is welcome to attend.

BE Doctoral Dissertation: "Characterizing medial temporal lobe neurodegeneration due to tau pathology in Alzheimer's Disease using postmortem imaging” (Sadhana Ravikumar)
2022-06-10 14:00 - 16:00 | BRB 0252
The Department of Bioengineering at the University of Pennsylvania and Dr. Paul Yushkevich are pleased to announce the Doctoral Dissertation Defense of Sadhana Ravikumar.

Title: “Characterizing medial temporal lobe neurodegeneration due to tau pathology in Alzheimer’s Disease using postmortem imaging”

Date: Friday, June 10th, 2022
Time: 2:00 PM
Location: Biomedical Research Building (BRB), Classroom 0252 and Zoom.

The public is invited to attend in-person or virtually at the link below:

Link: https://upenn.zoom.us/j/95448705068?pwd=[REDACTED]

Meeting ID: 954 4870 5068
Passcode: [REDACTED]

CBE PhD Dissertation Defense | "The effects of platelet signaling inhibitors on clot development under flow"
2022-06-10 15:00 - 16:30 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
“Syk and Src family kinases (SFK) inhibitors interfere with signaling from GPVI, α2β1, αIIbβ3, and GPIb-IX-V to reduce thrombotic risk or induce bleeding episodes. Collagen-mediated clustering of platelet GPVI results in phosphorylation of SFKs such as Lyn and Fyn, and active Lyn is constitutively bound to GPVI to allow rapid signaling. During clotting under flow, the generation of fibrin can have diverse influences on platelet signaling by sequestering thrombin and potentially activating GPVI signaling within the clot interior. These inhibitors tackle the thrombus formation at earlier stages since the platelets reach the activation surface. Direct inhibition of GPVI was used to compare the difference between inhibition of subsequent pathways. Using microfluidics, the effects of these inhibitors can be explored under defined hemodynamic flows and procoagulant surface triggers. Additionally, the drug may be present in the blood at desired time of clotting by perfusion switching to drug-treated blood. This experimental design allows exploration of platelet response at different stages of clotting through the measurement of drug potency to modulate clotting on different procoagulant surface conditions.“

BE Doctoral Dissertation Defense: "Machine Learning and Quantitative Neuroimaging in Epilepsy and Low-field MRI" (T. Campbell Arnold)
2022-06-13 10:30 - 12:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering and Dr. Brian Litt are pleased to announce the Doctoral Dissertation Defense of T. Campbell Arnold.
Monday, June 13, 2022
10:30 AM
The public is welcome to attend.

Room: Glandt Forum, Singh Center
Zoom link: https://upenn.zoom.us/j/91843511143?pwd=[REDACTED]
Meeting ID: 918 4351 1143
Passcode: [REDACTED]

PSOC@Penn Talk (TBA)
2022-06-13 12:00 - 13:00 | PA

CEMB Distinguished Lecture: Bioengineered Synthetic Hydrogels for Regenerative Medicine
2022-06-14 15:00 - 16:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The Center for Engineering MechanoBiology (CEMB) welcomes Dr. García for a Distinguished Lecture on June 14th at 3pm. A reception will follow the seminar in the Levine Lobby.

MSE Ph.D. Defense: "Understanding the Fracture Behavior of Polymer-infiltrated Nanoparticle Films" (Yiwei Qiang)
2022-06-14 15:00 - 17:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
Polymer-infiltrated nanoparticle films (PINFs) are a new class of polymer nanocomposites that overcome many of the challenges in manufacturing highly loaded nanocomposite films (PNCFs). PINFs have a wide range of applications as functional coatings and membranes and have excellent mechanical properties, including high stiffness, hardness, scratch and wear resistance. Fracture toughness is another critical mechanical property that plays an important role in the durability and reliability of PINFs. Establishing a fundamental understanding of the fracture behavior of PINFs is crucial to the design of damage tolerant PINFs.
In this work, the effect of particle shape, confinement, and polymer-nanoparticle (NP) interactions on the fracture behavior of PINFs is investigated. The results show that well-aligned, high aspect ratio (AR) nanoplatelet films have significantly higher fracture toughness and larger enhancement in modulus, hardness and scratch resistance upon polymer infiltration than low AR NP films. Using a thin-film fracture testing method based on the double cantilever beam specimen, the role of confinement on fracture toughness is investigated by tuning the polymer molecular weight (MW) and NP size. The effect of polymer-NP interaction strength is also investigated by varying the type of polymer and changing the surface chemistry of NPs. The results show that the polymers can significantly toughen NP films through a confinement-induced molecular bridging mechanism when they are under extreme confinement and completely lose interchain entanglement. This mechanism is controlled by polymer MW, pore size and polymer-NP interaction strength and ultimately limited by the strength of polymer backbone. As the degree of confinement decreases, the bridging mechanism becomes less pronounced. In this case, entanglement-based mechanism becomes dominant and the fracture toughness of PINFs is dependent on the fracture properties of polymers. Finally, it is shown that the fracture toughness of PINFs can be further enhanced using mesoporous NPs due to the increase of polymer-NP interaction area and the interlocking between the polymer and NPs via mesopores. Thus, this work provides important guidelines for the design of mechanically robust PINFs as well as other highly loaded PNCFs.
Dissertation Committee: Dr. Daeyeon Lee (Co-advisor), Dr. Kevin T. Turner (Co-advisor), Dr. Karen I. Winey and Dr. Robert A. Riggleman
Location: Attendees are welcome in person in Towne 337 and via Zoom: https://upenn.zoom.us/j/99675230377.

CEMB Future Leaders: "Sensing the force from within: the nucleus as regulator of migration plasticity"
2022-06-15 11:00 - 12:00 | https://upenn.zoom.us/j/96715197752
Launched in May 2021, the Future Leaders in Mechanobiology is a monthly seminar series featuring up-and-coming leaders in mechanobiology–PhD students and postdocs from a wide range of fields, backgrounds, and institutions. By providing an international stage to share one’s work and opportunities to interact with researchers at all career stages, we aim to create an inclusive and valuable series for early-stage researchers and the mechanobiology community as a whole.
Register HERE for access to the Zoom link and visit the CEMB website for more information.

Department of Bioengineering 2022 Juneteenth Address: "Perspectives on Diversity, Equity and Inclusion Through a Rehabilitation, Medicine and Robotics Research Lens" (Dr. Michelle Johnson)
2022-06-17 12:00 - 13:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Join the Department of Bioengineering for a Juneteenth Address delivered by Dr. Michelle Johnson, Associate Professor in Physical Medicine and Rehabilitation and in Bioengineering and Director of the Rehabilitation Robotics Lab. The address will be followed by a Q&A. This hybrid event will be held live on campus and on Zoom and is open to the entire Penn Bioengineering community.
Room: Towne 337
For Zoom link & passcode, check email or contact ksas@seas.upenn.edu.

MEAM Seminar: "Mobile Wireless Infrastructure on Demand in Robot Teams"
2022-06-21 10:00 - 11:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
The promise of multi-robot systems is that they can complete tasks quicker and more efficiently than a single robot. However, such performance gains are only realized if robots can communicate with each other and coordinate their actions. As on-board autonomy advances, robots are increasingly being deployed in environments without existing wireless infrastructure and must rely instead on peer-to-peer or ad-hoc networks in order to exchange information. In these scenarios, control actions taken to complete the task objective often move robots out of direct communication range of one another, introducing a tension between task fulfillment and communication network maintenance. In this seminar, I will present my work towards eliminating this tension and enabling multi-robot teams to operate in challenging environments by using robots as mobile wireless infrastructure.

PSOC@Penn Talk “Small fat droplets are sufficiently rigid to indent a nucleus, dilute the lamina, and cause rupture" (Irena Ivanoska)
2022-06-21 12:00 - 13:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Contact manu@seas.upenn.edu for the Zoom link.
Title: “Small fat droplets are sufficiently rigid to indent a nucleus, dilute the lamina, and cause rupture”

CT3N Seminar: "Design of Targeted Antimicrobials" (Christopher A. Alabi)
2022-06-22 12:00 - 13:00 | Smilow 10th Floor, Room 146AB
This hybrid seminar is hosted by the Center for Targeted Therapeutics and Translational Nanomedicine (CT3N)

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ESE Ph.D. Thesis Defense: "Machine Learning on Large-Scale Graphs"
2022-06-27 10:00 - 12:00 | Room 452 C, 3401 Walnut, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Graph neural networks (GNNs) are successful at learning representations from most types of network data but suffer from limitations in large graphs, which do not have the Euclidean structure that time and image signals have in the limit. Yet, large graphs can often be identified as being similar to each other in the sense that they share structural properties. Indeed, graphs can be grouped in families converging to a common graph limit — the graphon. A graphon is a bounded symmetric kernel which can be interpreted as both a random graph model and a limit object of a convergent sequence of graphs. Graphs sampled from a graphon almost surely share structural properties in the limit, which implies that graphons describe families of similar graphs. We can thus expect that processing data supported on graphs associated with the same graphon should yield similar results. In my research, I formalize this intuition by showing that the error made when transferring a GNN across two graphs in a graphon family is small when the graphs are sufficiently large. This enables large-scale graph machine learning by transference: training GNNs on moderate-scale graphs and executing them on large-scale graphs.

PSOC@Penn Talk: "Microtechnology-based Single Cell and EV Profiling” (Jina Ko)
2022-06-27 12:00 - 13:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

MEAM Ph.D. Thesis Defense: "Enhancing Strength and Toughness Via Reinforcement with Nanocellulose Fibers"
2022-06-28 10:00 - 11:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Cellulose nanofibrils (CNFs) are a nanomaterial obtained from plant sources and have excellent mechanical properties, high aspect ratios, and are biodegradable. As a reinforcing phase, CNFs have the potential to improve the mechanical properties of polymer materials. The overarching objective of this thesis is to investigate the use of CNFs to enhance the strength and toughness of polymers and traditional papers.
In the first part of this thesis, poly methyl methacrylate (PMMA) fibers are reinforced using CNFs to increase the strength and toughness. Fourier transform infrared (FTIR) spectroscopy is used to measure PMMA molecular orientation in the composite fibers. Tensile tests and fiber-based fracture tests using edge-cracked fibers are used to quantify the enhancement of modulus, strength, and fracture toughness through the addition of CNFs to PMMA. Specifically, a 2 improvement in fracture toughness is observed at 1% wt. CNF content.
In the second part of the thesis, filter paper, which is a network of microscale cellulose fibers is infiltrated with CNFs to create all-cellulose sheets with heterogenous mechanical properties. This is realized by printing and subsequent drying of an aqueous CNF solution and patterning of the infiltrated regions is used to engineer the strength and toughness of the materials. Single edge notch tension (SENT) tests are performed on the specimens to evaluate their fracture behavior. It is shown that geometric and elastic heterogeneity can be utilized to tune the toughness over a large range while maintaining or improving the strength.
Finally, to overcome limitations of the SENT, a new experimental fracture specimen, denoted the hinged rigid beam (HRB), was developed. The HRB eliminates the compressive stresses developed in conventional beam-bending fracture tests like the double cantilever beam method, thus making it suitable for testing thin materials such as paper. A mechanics model of the HRB was developed to allow critical strain energy release rate to be calculated from the measured force-displacement response and the specimen was validated via finite element analysis and experiments on thin PMMA sheets. This technique was used to characterize the toughness of several materials, including filter paper, copy paper and 2D lattice materials. Finally, the HRB was used to characterize and further understand the fracture behavior of patterned nanocellulose infiltrated sheets.

MEAM Seminar: "Mixing with Activity: Transport of Swimming Microorganisms in Complex Flows"
2022-07-05 10:00 - 23:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
How will swimming microorganisms affect the mixing of a diffusive contaminant in chaotic flows? Answers to this question can lead to improved understanding of the spread of pollutants (e.g. algal blooms) in oceans and lakes, as well as potentially useful applications in biofuel and vaccine productions. In this talk, I present recent experiments on the chaotic mixing of a passive pollutant in dilute suspensions of swimming Escherichia coli. I will first discuss the results in a two-dimensional (2D) time-periodic flow that preserves spatial symmetry. Second, I will extend these results to a more realistic case of spatially disordered 2D vortical flows that resemble geological flows in nature. Overall, these results show that the interaction between active swimming particles and dynamical structures of the flow (i.e. Lagrangian coherent structures) can lead to profound changes in the transport and mixing of passive scalar quantities.

Quantum Engineering Summer Seminar Series: Jon Felbinger, PhD [private-public partnerships] (Quantum Economic Development Consortium)
2022-07-08 12:00 - 13:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
About the Series: The Quantum Engineering Summer Seminar Series is hosted by the Quantum Engineering Graduate Association (QEGA) every Friday at 12:00 – 1:00 pm EDT throughout the summer months and will be followed by a separate Fall series. The series invites leading world leading experts across academia, industry, and government working on experimental, theoretical, and policy aspects of quantum science and engineering. Each seminar will be followed by a 10 minute networking session with the invited speaker.
Speaker List:
July 8th, 2022 – Jon Felbinger, PhD [private-public partnerships] (Quantum Economic Development Consortium)
July 15th, 2022 – William Oliver, PhD [superconducting qubits] (MIT and MIT Lincoln Labs)
July 22nd, 2022 – Sinead Griffin, PhD [novel qubit materials design] (Lawrence Berkeley National Laboratory)
July 29th, 2022 – Hannes Bernien, PhD [trapped ion systems] (University of Chicago)
August 5th, 2022 – Prineha Narang, PhD [computational quantum dynamics] (Harvard University)
August 12th, 2022 – Peter McMahon, PhD [quantum annealing] (Cornell University)
August 19th, 2022 – Nick Bronn, PhD [NISQ era quantum computing] (IBM)
August 26th, 2022 – Riccardo Manenti, PhD [scalable quantum computing systems] (Rigetti)
Meeting Information: The seminar series will be a hybrid event with talks broadcasted on campus (Wu and Chen Auditorium, Levine Hall) and available online via Zoom. The Zoom link will be posted weekly for each individual talk.
Join QEGA: The Quantum Engineering Graduate Association (QEGA) is a new organization at Penn founded by Nima Leclerc and Noah Johnson, two Penn ESE PhD students in the Sigillito Group. QEGA’s goal is to increase graduate student and faculty engagement in quantum engineering at Penn through school-wide events such as this seminar series, quantum-career networking opportunities, and a quantum engineering outreach program program. If you would like to stay connected with us, please email Nima at nleclerc@seas.upenn.edu with the subject line ‘qega listserv’ to get added to our mailing list!

PSOC@Penn: “Fat accumulation induces heterogeneous regions of softness in fatty liver” (David Li)
2022-07-11 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "Sedimentation of Active Suspensions: Hindrance and Phase-separation"
2022-07-12 10:00 - 11:30 | Towne 313, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Sedimentation of active matter is found in many natural and industrial processes. It plays an important role on the distribution of plankton in oceans, which is key part of the carbon cycle (i.e. ocean’s biological pump) that transports carbon from the ocean’s surface to depth. In this seminar, I will present an investigation on the dynamics of the sedimentation of spherical colloids in presence of swimming microorganisms at various concentration within the dilute regime. In the first part of this talk, I will show how bacterial activity hinders the sedimentation speeds of passive particle. These results can be described by an advection-diffusion equation with an added population dynamics term. In the second part of this talk, I will show the appearance of two sedimentation fronts, particle and bacterial. Even passive systems of poly-dispersed (by size) particles are known to show segregating sedimentation fronts; larger (and faster) settling particles will separate from smaller (and slower) ones, given enough time. Here, I will show how the increase of activity affects sedimentation speeds and the timescales associated with the appearance of the bacteria front. These timescales associated with the second front leads to a phenomenological model that captures the sedimentation of passive particles in active fluids.

ESE Ph.D. Thesis Defense: "Optical and Spin Dynamics of Quantum Emitters in Hexagonal Boron Nitride at Room Temperature"
2022-07-13 10:00 - 11:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Hexagonal boron nitride (h-BN) is a van der Waals material that hosts defect-based quantum emitters (QEs) at room temperature, providing an unparalleled platform for realizing devices for quantum technologies and studying light-matter interactions. Recent observations suggest the existence of multiple distinct defect structures responsible for QEs. Theoretical proposals suggest vacancies, substitutional atoms, and their complexes as likely defect candidates. However, experimental identification of the QEs’ electronic structure is lacking, and key details of the QEs’ charge and spin properties remain unknown. This thesis focuses on understanding the optical and spin dynamics of QEs in h-BN at room temperature. Starting with the motivation for studying quantum systems and QEs, this thesis introduces QEs in h-BN and discusses its current understanding. Next, it discusses the materials and methods developed and utilized during the course of this thesis. Next, it discusses the optical dynamics acquired using photoluminescence spectroscopy and photon emission correlation spectroscopy (PECS) and shows several QEs exhibit pure single-photon emission. It discusses the complex optical dynamics associated with excitation and relaxation through multiple electronic excited states – revealed by PECS and polarization-resolved excitation and emission. Following, it presents the optical dynamics simulations of electronic structure models that are consistent with the observations, and discusses the results in the context of ab initio theoretical calculations. Next, it discusses magnetic-field-dependent PECS that can be used as a framework to probe the presence of single spins that are otherwise elusive. Following, it presents detection and confirmation of single-spin using optically detected magnetic resonance. Finally, it discusses the spin dynamics and time-domain measurements acquired using optical and microwave pulse protocols crucial to developing methods to coherently control the QE’s spin. To conclude, it discusses the future directions that can help identify the chemical nature of QEs in h-BN and establish it as a scalable material platform for quantum technologies.

ESE Ph.D. Thesis Defense: "Learning Environmental Models with Multi-Robot Teams Using a Dynamical Systems Approach"
2022-07-14 10:00 - 12:00 | PERCH 303, Pennovation 3rd Floor, 3401 Grays Ferry Avenue, Bldg 6176, Philadelphia, PA, 19146, United States
Robots have the capability to sense and track natural phenomena for environmental monitoring, deepening our understanding of the world. Robotic modeling of such phenomena is essential to operating in complex environments, allowing robots to perform in more realistic scenarios. Thus, representing complex environments is paramount to the success of multi-robot teams. While considerable efforts have been made for modeling with multi-robot teams, specifically in coordination and distributed methods, these techniques have limitations in spatiotemporal, complex environments. These environments can be vastly different, such as fluid flows, oceans, and space. Robots operating in these environments typically create representations of their surroundings using computationally expensive techniques or by leveraging human expert knowledge.
Interestingly, though these environmental processes may seem unrelated, they can all be analyzed with dynamical systems theory. This thesis presents methods for representing the environment as a dynamical system with machine learning techniques. We formulate machine learning methods that lend to data-driven modeling of the phenomena for robotic applications, specifically using dimensionality reduction techniques and kernel methods. The data-driven modeling explicitly leverages theoretical foundations of dynamical systems theory. Dynamical systems theory offers mathematical and physically interpretable intuitions about the environmental representation. The procedures presented include distributed algorithms, online adaptation, uncertainty quantification, and feature extraction to allow for the actualization of these techniques on-board robots. The environmental representations guide robot behavior in developing strategies such as optimal sensing and energy-efficient navigation. The methods and procedures provided in this thesis were verified across prototypical environments and on experimental robots.
