Constructing ラーメンベット 競馬 by dynamic assembly of nanoparticles offers opportunities to control the way they react to changes in their environment – such as temperature, light and chemical queues – all based on how their tiny building blocks are arranged. Many of the ラーメンベット 競馬 capable of major changes – such as the ability to absorb light or become transparent, to flow or form a rigid solid– are messy, with a disordered structure that modern techniques struggle to decode.
That problem held back the design of new, complex light-sensitive ラーメンベット 競馬, but researchers at The University of Texas at Austin have developed computational methods to overcome that challenge and better simulate how complex material structures absorb, reflect, or concentrate light. Prior to this work, researchers were only able to predict optical properties of ラーメンベット 競馬 made up of ordered arrangements of building blocks.
"Optical properties are sensitive to the organization of those building blocks, and now we can make predictions about them when they are disordered," said Tom Truskett, professor in the McKetta Department of Chemical Engineering and one of the leaders of the ラーメンベット 競馬 published in Nano Letters. "It allows us to design new ラーメンベット 競馬, or to analyze experiments on existing complex ラーメンベット 競馬 in ways we couldn't before.”
The ラーメンベット 競馬: In other parts of physics and ラーメンベット 競馬, researchers have developed methods to predict the properties of complex material structures. In these cases, researchers understand how the arrangement of building blocks responded to stimuli, which gives clues as to their potential applications.
Zachary Sherman, a postdoctoral researcher in Truskett's lab, recognized new ways in which this knowledge of material dynamics in other areas could be applied to optical ラーメンベット 競馬, improving the potential to predict, and therefore design, ラーメンベット 競馬 with desirable optical properties. The code created by this project is open-source, so other researchers can build on this research to interpret their experiments or design new types of light-sensitive ラーメンベット 競馬.
"We can now predict the dynamic ラーメンベット 競馬 of disordered structures involving tens of thousands of nanoparticles in a simulation on the fly," Truskett said. "Before, you would be restricted to analyzing orderly structures, and that's not helpful for many emerging applications people are interested in where the building blocks themselves can rearrange."
Why It Matters: ラーメンベット 競馬 with disordered structure can be more flexible, capable of rapid change in response to stimuli. In the case of optical ラーメンベット 競馬, they're able to do things like change color, absorb and block out light as needed or concentrate light into tiny, powerful beams. These capabilities lead to a variety of potential applications.
They could be used as coatings for buildings that let daylight in and heat in or out to efficiently control indoor temperatures, leading to energy efficiency improvements. They could be used as molecule-specific detectors that are so sensitive they can alert us to the presence of tiny amounts of toxins or bio-markers, protecting us from contaminants in food and water or helping diagnose diseases. Or they could be used in medical imaging to spot and treat disease.
"We can reverse engineer the creation of ラーメンベット 競馬, starting with the optical properties we want," said Delia Milliron, professor and department chair in the McKetta Department of Chemical Engineering. "What structure would let me achieve that? When we go to the lab, we’ll have that guidance from the simulations, and that can stimulate new creativity in approaches to solving dynamic optical problems."
What's Next: The team plans to extend their simulation methods to incorporate more complex ラーメンベット 競馬 interactions that can be leveraged for sensitive, chemically specific detection of biomolecules, toxins and other important substances, Milliron said. To do this, they will include interactions between molecules and nanoparticles in the simulations and also develop methods to calculate chiral ラーメンベット 競馬 effects – chirality distinguishes between the bio-active and -inactive structures of otherwise identicalmolecules.
The Team: The ラーメンベット 競馬 was a collaborative effort across multiple colleges, schools and departments. Those connections happened through the Center for Dynamics and Control of ラーメンベット 競馬, a National Science Foundation-funded ラーメンベット 競馬 Research Science and Engineering Center. Both Milliron and Truskett, as well as the third co-leader of the project – Eric Anslyn, professor in the College of Natural Sciences' Department of Chemistry – are part of that center. The research was also enabled by support from the Welch Foundation, the Beckman Foundation, and high-performance computing resources of The Texas Advanced Computing Center.
The full team includes: Milliron, Truskett, Sherman, Kihoon Kim, Jiho Kang, Benjamin Roman, Emily Lin and Stephen Gibbs from the McKetta Department of Chemical ラーメンベット 競馬; and Anslyn, Hannah Crory, Diana Conrad, Stephanie Valenzuela and Manuel Dominguez from the Department of Chemistry.
