Sleuthing Their Way to Discovery with a New Microscope
Chemists magnify molecular clarity of hydrogen-bond interactions to boost biomimetics
- Cynthia Dillon
- Cynthia Dillon - firstname.lastname@example.org
- Cynthia Dillon
As a magnifying lens is to a detective, a microscope is to a chemist. These tools of trade help both investigator-types follow the evidence. In the case of a detective, it’s to find the marks of a criminal; in the case of a chemist—at least for UC San Diego’s Wei Xiong—it’s to discover molecular properties that influence chemical reactions and materials’ functions.
When it comes to gathering clues, Xiong hunts down miniscule molecules that aren’t easy to see, which is why he and his team of researchers developed a microscope that gives them a thorough view of molecular systems—not just single traits of molecules. Their project’s results are now published in an
The novel tool
The microscope helped the scientists see that different self-assemblies can have distinct H-bond interactions, depending on their levels of hydration. Additionally, the scientists found that the H-bond interactions are ordered in the self-assemblies, i.e., the H-bond only exists with certain molecular groups, while other groups nearby don’t have it.
“On the other hand, the H-bond can break and restore fast—on the hundreds of the femtosecond time scale,” said Xiong. “We believe the local ordering and fast dynamics of H-bond is the key for this material to mimic biological crystallinity and flexibility, and thereby the local hydration of each self-assembly set determines the unique H-bond interactions and its distinct mechanical properties. This fundamental knowledge offers guidelines to further develop biomimetic materials for biomedical applications.”
Xiong said that one hypothesis is that H-bond interaction between water and the materials is essential. Since the H-bond interaction in these materials is ultrafast (at the femtosecond to picosecond scale), multiple interactions’ dependency on the morphology, or form, of the self-assemblies has not been studied much, he noted. Therefore, the team’s new microscopy technique is positioned to resolve this question from multiple aspects.
“The development and demonstration of this technique make it available for other chemical systems, such as aerosol surfaces, which are related to environment and public health,” noted Xiong.
Xiong said they overcame this difficulty by first analyzing the data on a coarse level and then selecting the interesting data point to perform detailed analysis. In the future, he expects to combine it with artificial intelligence (AI).
“Because we applied a new tool on new material, distilling the key and new molecular physics was the final challenge,” said Xiong. “This step occurred during COVID, and Haoyuan and I spent a lot of time on Zoom and exchanged emails until we developed a simple and intuitive model to covert the H-bond dynamics into local hydration level, demonstrating the critical new insights we can learn using this technique.”
Wang said that during the study they struggledXiong noted that Wang had just joined the group when the project began, so he had little knowledge of the instrument. Still, he introduced the unique self-assembled system, which is the core system the group studied.
“I still remember it was right before Christmas, and I was on my way to join the department party at Price Center,” said the PhD student. “But when I was halfway, I realized a method to resolve the problem. I shouted to myself and ran back to the lab to test my thought immediately. Though I missed the department party, I enjoyed that moment when I got inspired.”
“Along with figuring out every detail of this project over several years, I became a more experienced mentor, and Haoyuan became an expert in nonlinear optics and came up with many brilliant ideas to tackle the technical and scientific difficulties we faced during this project,” said Xiong, who said he enjoyed seeing how all the students involved grew through the process. “
Other members of the Xiong Group who contributed to this research included Jackson Wagner, Wenfan Chen and Chenglai Wang. This study was supported by DARPA (D15AP00107); DOE, BES (DE-SC0019333) and NSF (CHE-1801971, CHE-1808111 and CHE-1828666).
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