skip to main content


Search for: All records

Creators/Authors contains: "Li, Yuxin"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Free, publicly-accessible full text available June 1, 2024
  2. null (Ed.)
    Crystal structure prediction is now playing an increasingly important role in the discovery of new materials or crystal engineering. Global optimization methods such as genetic algorithms (GAs) and particle swarm optimization have been combined with first-principles free energy calculations to predict crystal structures given the composition or only a chemical system. While these approaches can exploit certain crystal patterns such as symmetry and periodicity in their search process, they usually do not exploit the large amount of implicit rules and constraints of atom configurations embodied in the large number of known crystal structures. They currently can only handle crystal structure prediction of relatively small systems. Inspired by the knowledge-rich protein structure prediction approach, herein we explore whether known geometric constraints such as the atomic contact map of a target crystal material can help predict its structure given its space group information. We propose a global optimization-based algorithm, CMCrystal, for crystal structure (atomic coordinates) reconstruction based on atomic contact maps. Based on extensive experiments using six global optimization algorithms, we show that it is viable to reconstruct the crystal structure given the atomic contact map for some crystal materials, but more geometric or physicochemical constraints are needed to achieve the successful reconstruction of other materials. 
    more » « less
  3. Here, we developed a microfluidic electrochemical flow cell for fast-scan cyclic voltammetry which is capable of rapid on-chip dilution for efficient and cost-effective electrode calibration. Fast-scan cyclic voltammetry (FSCV) at carbon-fiber microelectrodes is a robust electroanalytical technique used to measure subsecond changes in neurotransmitter concentration over time.Traditional methods of electrode calibration for FSCV require several milliliters of a standard. Additionally, generating calibration curves can be time-consuming because separate solutions must be prepared for each concentration. Microfluidic electrochemical flow cells have been developed in the past; however, they often require incorporating the electrode in the device, making it difficult to remove for testing in biological tissues. Likewise, current microfluidic electrochemical flow cells are not capable of rapid on-chip dilution to eliminate the requirement of making multiple solutions. We designed a T-channel device, with microchannel dimensions of 100 μm × 50 μm, that delivered a standard to a 2-mm-diameter open electrode sampling well. A waste channel with the same dimensions was designed perpendicular to the well to flush and remove the standard. The dimensions of the T-microchannels and flow rates were chosen to facilitate complete mixing in the delivery channel prior to reaching the electrode. The degree of mixing was computationally modeled using COMSOL and was quantitatively assessed in the device using both colored dyes and electrochemical detection. On-chip electrode calibration for dopamine with FSCV was not significantly different than the traditional calibration method demonstrating its utility for FSCV calibration. Overall, this device improves the efficiency and ease of electrode calibration. 
    more » « less