Wisconsin MRSEC researchers have developed a coarse-graining technique called AniSOAP (for anisotropic smooth overlap of atomic potentials) that gives the beads shapes that reflect the shape of the molecules they represent. This simple idea – carefully implemented to be mathematically rigorous and account for how molecules typically interact – can used for high-accuracy coarse grained simulations or to understand materials behavior that depends on molecular shape or orientation. AniSOAP is also particularly useful for machine learning analysis of molecular behavior using simple, physically-interpretable algorithms, producing new insight for researchers.
IRG 1
(2025) A Nanoscale View of Molecule Alignment in an Organic Semiconductor
Wisconsin MRSEC researchers have developed a new way to see how molecules fit together with an electron microscope. They used the method to see how molecules rearrange when an organic semiconductor is heated. A modest change in temperature creates significantly improved molecular alignment. The improved alignment is reflected in both larger aligned regions and straighter lines of molecules inside each region.
(2024) Control of Glass Structure and Properties with Soft Substrates
Physical vapor deposition (PVD) canproduce glassthinfilmswith preferred orientation to the molecules andhigherdensitythan ordinaryliquid-quenchedglass bytakingadvantageofthefastmovementoforiented moleculesonthe glasssurface.
Research supported by Wisconsin MRSEC have found a new way to control the structure and properties of these films by growing them on soft substrates. PVD on a soft substrate can produce glass thin films that are much more dense and stable than those deposited on rigid substrates. A film deposited on a soft substrate in 2 hours is equivalent to a film deposited extremely slowly on rigid substrates over ~3000 years.
(2024) Biaxially-aligned Glasses of Organic Semiconductors
Download PDF
MRSEC Graduate Student Gives Two Presentations at IMC20
Shuoyuan Huang, a graduate student in Paul Voyles’ lab, recently attended the 20th International Microscopy Congress in Busan, Korea. While there, he presented two talks: “Momentum-Resolved Electron Correlation Microscopy Reveals Structure Dependent Dynamics in Metallic Supercooled Liquids” and “High-speed, Low-dose 4D STEM of Orientation Domains in an Anisotropic Molecular Glass.”
(2021) New Insights into Surface Diffusion on Glasses
Understanding how atoms move is fundamental to making and using materials. Atoms on the surface of some glasses move at nearly the same rate as atoms on the inside. But for other glasses, surfaces atoms move a million times faster. Researchers in the Wisconsin MRSEC IRG 1 have combined experiments, simulations, and data-centric methods to understand why some surfaces are so much faster than others. They found that atoms in glasses move by breaking out of a “cage” of nearby atoms. On the surface, that cage can be weaker than inside the glass, allowing for faster motion. They also discovered a relationship that predicts surface motion from more accessible data about bulk motion. Their results unify behavior for glasses of organic molecules, metals, and oxides and make creating glasses for applications like light-emitting diodes, quantum computers, and hard coatings easier.
(2021) Use Machine Learning to Link Atomic Structure with Glass Properties and Behaviors
Glasses have disordered arrangements of atoms without the repeating patterns that crystals have. However, there are small-scale patterns of atoms that touch each other that strongly affect the energy of the glass, how the atoms move when they get hot, and other properties like strength and response to an electric field. Unfortunately, there are many possible patterns and many slight variations of each one, so studying them is like sorting the grains of sand on a beach by size and color by hand–it’s an impossible task. Wisconsin MRSEC IRG 1 uses machine learning to sort the sand. They have developed algorithms to find small-scale atomic patterns in large simulations of glasses and link them to the glass’ energy. Ongoing studies have connected patterns to atomic motions, which provides a path to simulations of glasses over long times and low temperatures that are currently impossible.
Large Dataset on the Relationship Between Structure and Stability in Glass Wins Open Science Award for Yu
The generation and sharing of a large dataset created as part of his study has won Zheng Yu the 2021 Wisconsin MRSEC Excellence in Open Science Prize. A graduate student in Dr. Bu Wang’s lab at the Grainger Institute for Engineering, Yu generated the data as part of his work investigating the relationship between structure and stability in specialized glasses using computer simulations and machine learning.
(2020) Order From Disorder: Molecular Packing in Glasses
Using physical vapor deposition, researchers produced glassy films that are smooth and uniform, but which also have the molecules aligned with one another and organized in layers. This added structure could make the glass more efficient for conductors and expand the range of materials that can be used in future organic electronics. The colorful images in the figure show measurements using synchrotron x-rays that contrast the disordered starting material and the ordered glass.
(2020) Why Sound Waves Travel So Far Unimpeded in Glasses at Low Temperatures
IRG 1 showed how the atoms around the defects can restrict their ability to jump between configurations and how defects can talk to each other via sound waves. Both phenomena keep the defects from interfering with sound waves allowing the waves to travel long distances.