@article{neupane_zhong_wang_2020, title={Study on self-assembly of colloidal particles at high ionic strength with stimulated emission depletion microscopy}, volume={2}, ISSN={["2577-8196"]}, DOI={10.1002/eng2.12233}, abstractNote={Abstract}, number={9}, journal={ENGINEERING REPORTS}, author={Neupane, Bhanu B. and Zhong, Yaning and Wang, Gufeng}, year={2020}, month={Sep} }
 @article{zhong_wang_2020, title={Three-Dimensional Single Particle Tracking and Its Applications in Confined Environments}, volume={13}, ISSN={["1936-1335"]}, DOI={10.1146/annurev-anchem-091819-100409}, abstractNote={ Single particle tracking (SPT) has proven to be a powerful technique in studying molecular dynamics in complicated systems. We review its recent development, including three-dimensional (3D) SPT and its applications in probing nanostructures and molecule-surface interactions that are important to analytical chemical processes. Several frequently used 3D SPT techniques are introduced. Especially of interest are those based on point spread function engineering, which are simple in instrumentation and can be easily adapted and used in analytical labs. Corresponding data analysis methods are briefly discussed. We present several important case studies, with a focus on probing mass transport and molecule-surface interactions in confined environments. The presented studies demonstrate the great potential of 3D SPT for understanding fundamental phenomena in confined space, which will enable us to predict basic principles involved in chemical recognition, separation, and analysis, and to optimize mass transport and responses by structural design and optimization. }, journal={ANNUAL REVIEW OF ANALYTICAL CHEMISTRY, VOL 13}, author={Zhong, Yaning and Wang, Gufeng}, year={2020}, pages={381–403} }
 @article{zhong_li_zhou_wang_2018, title={Developing Noise-Resistant Three-Dimensional Single Particle Tracking Using Deep Neural Networks}, volume={90}, ISSN={["1520-6882"]}, DOI={10.1021/acs.analchem.8b01334}, abstractNote={Three-dimensional single particle tracking (3D SPT) is a powerful tool in various chemical and biological studies. In 3D SPT, z sensitive point spread functions (PSFs) are frequently used to generate different patterns, from which the axial position of the probe can be recovered in addition to its xy coordinates. Conventional linear classifier-based methods, for example, the correlation coefficient method, perform poorly when the signal-to-noise ratio (S/N) drops. In this work, we test deep neural networks (DNNs) in recognizing and differentiating very similar image patterns incurred in 3D SPT. The training of the deep neural networks is optimized, and a procedure is established for 3D localization. We show that for high S/N images, both DNNs and conventional correlation coefficient-based method perform well. However, when the S/N drops close to 1, conventional methods completely fail while DNNs show strong resistance to both artificial and experimental noises. This noise resistance allows us to achieve a camera integration time of 50 μs for 200 nm fluorescent particles without losing accuracy significantly. This study sheds new light on developing robust image data analysis methods and on improving the time resolution of 3D SPT.}, number={18}, journal={ANALYTICAL CHEMISTRY}, author={Zhong, Yaning and Li, Chao and Zhou, Huiyang and Wang, Gufeng}, year={2018}, month={Sep}, pages={10748–10757} }
 @article{zhong_wang_2018, title={Three-Dimensional Heterogeneous Structure Formation on a Supported Lipid Bilayer Disclosed by Single-Particle Tracking}, volume={34}, ISSN={["0743-7463"]}, DOI={10.1021/acs.langmuir.8b01690}, abstractNote={Three-dimensional (3D) single-particle tracking was employed to study the lipid membrane morphology change at different pHs on glass supported lipid bilayers (SLBs) [1,2-dioleoyl- sn-glycero-3-phosphoethanolamine/1,2-dioleoyl- sn-glycero-3-phospho-l-serine (sodium salt)/1,2-dioleoyl- sn-glycero-3-phosphocholine = 5:3:2]. Fluorescently tagged, carboxylated polystyrene nanoparticles (of 100 nm) were used as the probes. At neutral pHs, the particles' diffusion was close to two-dimensional Brownian motion, indicating a mainly planar structure of the SLBs. When the environmental pH was tuned to be basic at 10.0, transiently confined diffusions within small areas were frequently observed. These confinements had a lateral dimension of 100-200 nm. Most interestingly, they showed 3D bulged structures protruding from the planar lipid bilayer. The particles were trapped by these 3D structures for a short period of time (∼0.75 s), with an estimated escape activation energy of ∼4.2 kB T. Nonuniform distribution of pH-sensitive lipids in the membrane was proposed to explain the formation of these 3D heterogeneous structures. This work suggests that the geometry of the 3D lipid structures can play a role in tuning the particle-lipid surface interactions. It sheds new light on the origin of lateral heterogeneity on the lipid membrane.}, number={39}, journal={LANGMUIR}, author={Zhong, Yaning and Wang, Gufeng}, year={2018}, month={Oct}, pages={11857–11865} }
 @article{zhong_zhao_tyrlik_wang_2017, title={Investigating Diffusing on Highly Curved Water-Oil Interface Using Three-Dimensional Single Particle Tracking}, volume={121}, ISSN={["1932-7447"]}, DOI={10.1021/acs.jpcc.7b01721}, abstractNote={Diffusion on highly curved surfaces is important to many industrial and biological processes. Despite the progress made in theoretical studies, how diffusion is affected by the curvature is unclear due to experimental challenges. Here, we measured the trajectories of polystyrene nanoparticles diffusing on highly curved water-silicone oil interface, where the oil droplet diameter ranges from several μm to as small as ∼400 nm. To analyze the diffusion coefficients on curved surface, an analytical solution developed by Castro-Villarreal containing an infinite series can be used. Through Monte Carlo simulations, we simplified the Castro-Villarreal equation and defined the conditions that satisfy corresponding approximations. For the experiments, unexpectedly, we found that the diffusion slows down significantly when the oil droplet becomes smaller. Possible reasons were discussed, and a diffusion-induced droplet deformation and interface fluctuation model is consistent with the experimental results. This stud...}, number={14}, journal={JOURNAL OF PHYSICAL CHEMISTRY C}, author={Zhong, Yaning and Zhao, Luyang and Tyrlik, Paul M. and Wang, Gufeng}, year={2017}, month={Apr}, pages={8023–8032} }
 @article{zhao_zhong_wei_ortiz_chen_wang_2016, title={Microscopic Movement of Slow-Diffusing Nanoparticles in Cylindrical Nanopores Studied with Three-Dimensional Tracking}, volume={88}, ISSN={["1520-6882"]}, DOI={10.1021/acs.analchem.5b04944}, abstractNote={To study slow mass transport in confined environments, we developed a three-dimensional (3D) single-particle localization technique to track their microscopic movements in cylindrical nanopores. Under two model conditions, particles are retained much longer inside the pores: (1) increased solvent viscosity, which slows down the particle throughout the whole pore, and (2) increased pore wall affinity, which slows down the particle only at the wall. In viscous solvents, the particle steps decrease proportionally to the increment of the viscosity, leading to macroscopically slow diffusion. As a contrast, the particles in sticky pores are microscopically active by showing limited reduction of step sizes. A restricted diffusion mode, possibly caused by the heterogeneous environment in sticky pores, is the main reason for macroscopically slow diffusion. This study shows that it is possible to differentiate slow diffusion in confined environments caused by different mechanisms.}, number={10}, journal={ANALYTICAL CHEMISTRY}, author={Zhao, Luyang and Zhong, Yaning and Wei, Yanli and Ortiz, Nathalia and Chen, Fang and Wang, Gufeng}, year={2016}, month={May}, pages={5122–5130} }