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Highlights

Top: 2022 inaugural DEEPenn STEM cohort  /  Bottom: Zahra Fakhraai, LRSM faculty and professor of Chemistry at Penn, speaking to participants during the faculty research talk segment of the DEEPenn STEM weekend. Image source: Felice Macera
Top: 2022 inaugural DEEPenn STEM cohort / Bottom: Zahra Fakhraai, LRSM faculty and professor of Chemistry at Penn, speaking to participants during the faculty research talk segment of the DEEPenn STEM weekend. Image source: Felice Macera
Jul 5, 2023
UPENN Materials Research Science and Engineering Centers

UPENN Outreach: Supporting Diversity, Equity, and Engagement in STEM

Mark Licurse & Ashley Wallace, University of Pennsylvania

The LRSM spearheaded the inaugural Diversity Equity Engagement at Penn in STEM (DEEPenn STEM) weekend in October 2022. The initiative aims to proactively educate and recruit students from ethnically and racially minoritized communities (i.e. URMs), women, and first-generation low-income (FGLI) students to STEM-related graduate programs at Penn. 
Damilola Lawal, from the Raney lab, demonstrates The Utility of Instability to a K-12 student. Image source: Felice Macera
Damilola Lawal, from the Raney lab, demonstrates The Utility of Instability to a K-12 student. Image source: Felice Macera
Jul 5, 2023
UPENN Materials Research Science and Engineering Centers

UPENN Outreach: 12th Annual Philadelphia Materials Day

Mark Licurse & Ashley Wallace, University of Pennsylvania

Philadelphia Materials Day is a collaborative effort between the University of Pennsylvania MRSEC and the Materials Science & Engineering Department at Drexel University to promote materials research in the region. The 12th annual Philadelphia Materials Day took place on February 11, 2023 at the Bossone Research Center at Drexel University.
The hyperdimensional spin–orbit laser: Today’s quantum communication devices use qubits, which can store two kinds of information at the same time. But this is not enough to hold much information or avoid noise. This study reports the development of an on-chip microfabricated laser that makes qudits, which are light particles with four kinds of information simultaneously. The more kinds of information, the better the quantum communication device can work in the real world.
The hyperdimensional spin–orbit laser: Today’s quantum communication devices use qubits, which can store two kinds of information at the same time. But this is not enough to hold much information or avoid noise. This study reports the development of an on-chip microfabricated laser that makes qudits, which are light particles with four kinds of information simultaneously. The more kinds of information, the better the quantum communication device can work in the real world.
Jul 5, 2023
UPENN Materials Research Science and Engineering Centers

UPENN Seed: Adding new dimensions to quantum communication

Liang Feng and Ritesh Agarwal, University of Pennsylvania

Researchers at the University of Pennsylvania have made a microfabricated laser using semiconductor fabrication methods that can control two features of the light particles: their orbit and their spin. This allows them to make light particles with four states simultaneously. These higher-dimensional quantum bits (qudits) can store more information and better avoid noise. They can also make quantum communication more secure and faster and allow more secure communications.
Physics-driven electronic learning machine. (Left) One variable-resistor edge with circuity to adjust its resistance each clock cycle.  (Right) A randomly-connected network of fifteen such edges as the repeat unit.  (Bottom) The three red nodes are designed as the inputs and the three open nodes are designated as the outputs. During the training phase for an “allostery” task, specific voltages are applied to the inputs, and the edges self-adjust until the output nodes evolve to the desired values. Regression and classification tasks were also demonstrated using appropriate supervision during the training phase.
Physics-driven electronic learning machine. (Left) One variable-resistor edge with circuity to adjust its resistance each clock cycle. (Right) A randomly-connected network of fifteen such edges as the repeat unit. (Bottom) The three red nodes are designed as the inputs and the three open nodes are designated as the outputs. During the training phase for an “allostery” task, specific voltages are applied to the inputs, and the edges self-adjust until the output nodes evolve to the desired values. Regression and classification tasks were also demonstrated using appropriate supervision during the training phase.
Jul 5, 2023
UPENN Materials Research Science and Engineering Centers

UPENN Seed: An electronic metamaterial capable of decentralized physics-driven learning

Douglas Durian and Andrea Liu, University of Pennsylvania

In conventional machine learning, a computer is used to minimize a cost function that specifies a desired task, using global information about the entire network. We have now demonstrated how machine learning tasks can be learned and performed without either a computer or global information by taking advantage of physics via a scheme called coupled learning1. Specifically, twin variable-resistor networks are run under different boundary conditions and corresponding edges are compared against only each other for determining resistance updates2.
Fig. 1. (a) Optical images of a temperature responsive LCE spindle microparticle. (b) Schematic of directed bending of a soft matrix embedded with LCE microparticles.  (c) (L) Bright-field microscopy images of the dually responsive LCE microparticles programmed with different orientations under the magnetic field. (M) Photographs of the initially flat sheet that bends along the in-plane directions at 180oC with cuts along the intersections. Cut length: 0.4 cm. (R) Finite element simulations of the bent film. Sample size is 1 cm x 1 1 cm x 200 μm.
Fig. 1. (a) Optical images of a temperature responsive LCE spindle microparticle. (b) Schematic of directed bending of a soft matrix embedded with LCE microparticles. (c) (L) Bright-field microscopy images of the dually responsive LCE microparticles programmed with different orientations under the magnetic field. (M) Photographs of the initially flat sheet that bends along the in-plane directions at 180oC with cuts along the intersections. Cut length: 0.4 cm. (R) Finite element simulations of the bent film. Sample size is 1 cm x 1 1 cm x 200 μm.
Jul 5, 2023
UPENN Materials Research Science and Engineering Centers

UPENN IRG3 Shape morphing directed by spatially encoded, dually responsive liquid crystalline elastomer micro-actuators

Shu Yang and Chris Murray, University of Pennsylvania

Liquid crystal elastomers (LCEs) with intrinsic molecular anisotropy can be preprogrammed to morph shapes from 2D to 3D under external stimuli. However, it is difficult to program the positions and orientations of individual building blocks separately and locally as they are chemically linked in the polymer network.
A fluorescent optical micrograph showing how vimentin networks (green) respond to compressive loads, and protect the cell nucleus from mechanical damage
A fluorescent optical micrograph showing how vimentin networks (green) respond to compressive loads, and protect the cell nucleus from mechanical damage
Jul 5, 2023
UPENN Materials Research Science and Engineering Centers

UPENN IRG2 Vimentin filaments protect cell nuclei from mechanical damage

Ekaterina Grishchuk and Paul Janmey, University of Pennsylvania

Cells and tissues are subjected to external mechanical stresses in the body, including compressive loads, pressure gradients, and shear. This study shows that single cells become harder when compressed and that the parts inside the cells that make them strong (called the cytoskeleton) change when they are compressed. Some cells, like fibroblasts, become harder when subjected to moderate compression. However, this does not happen if a part of the cytoskeleton called vimentin is removed. This is because vimentin networks become harder when compressed or extended. This is explained using a theoretical model to based on the flexibility of vimentin filaments and their surface charge, which resists volume changes of the network under compression.
Jul 5, 2023
UPENN Materials Research Science and Engineering Centers

Fabricating Granular Hydrogels for 3D Printing

Paulo Arratia, University of Pennsylvania / Jason Burdick, University of Colorado

Granular hydrogels are jammed assemblies of hydrogel microparticles (i.e., “microgels”) widely explored in biomedical applications due to promising features such as shear-thinning to permit injectability and inherent porosity for cellular interactions. One area where this is particularly promising is in 3D printing. 
Image source: © Denis Linine from Pexels (Alps) and © Pears2295 for Getty Images  (Grand Canyon)
Image source: © Denis Linine from Pexels (Alps) and © Pears2295 for Getty Images (Grand Canyon)
Jul 5, 2023
UPENN Materials Research Science and Engineering Centers

Uncovering the Surprising Nature of Glassy Energy Landscapes

John C. Crocker (CBE) and Robert A. Riggleman (CBE), University of Pennsylvania

UPenn researchers explored the potential energy landscapes of three different glassy and glass-forming model systems in simulation; discovering that the lowest energy glassy states of the system have an unexpected arrangement in high-dimensional configuration space.  Specifically, rather than being randomly scattered and separated by steep and tall energy barriers (akin to the lowest points in an Alpine landscape), the states were arranged into quasi-one-dimensional clusters, crumpled into a fractal shape, with only small barriers between them (akin to the low-lying points along the floor of the Grand Canyon). 
For PINFs with small nanoparticles, bridging is the dominant toughening mechanism. In contrast, for PINFs with large nanoparticles, chain entanglement in the pores of disordered packings of nanoparticles is the main mode of toughening.
For PINFs with small nanoparticles, bridging is the dominant toughening mechanism. In contrast, for PINFs with large nanoparticles, chain entanglement in the pores of disordered packings of nanoparticles is the main mode of toughening.
Jul 5, 2023
UPENN Materials Research Science and Engineering Centers

Toughening Infiltrated Nanoparticle Packings: Role of Bridging and Entanglement

Kevin Turner, Daeyeon Lee, University of Pennsylvania

Researchers at UPenn investigate the fracture behavior of disordered polymer-infiltrated nanoparticle films (PINFs). Here, the extent of polymer confinement in PINFs was tuned over three orders of magnitude NPs of varying size and polymers with varying molecular weight. The results show that brittle, low molecular weight (MW) polymers can significantly toughen NP packings, and this toughening effect becomes less pronounced with increasing NP size. 
Jun 12, 2023
University of Washington Molecular Engineering Materials Center

MEM-C IRG-2: Nematic Fluctuations in an Orbital Selective Superconductor Fe1+yTe1-xSex

Xiaodong Xu, Jiun-Haw Chu

Electronic  nematicity  is  a  correlated  electronic  state  in  solids  that spontaneously breaks rotational symmetry. This work found that in Fe1+yTe1-xSex,  one  of  the  most  strongly  correlated  iron-based superconductors,   electronic   nematicity   is   closely   linked   to magnetism,   and   its   fluctuations   may   be   responsible   for superconducting pairing.