Three-Dimensional Tracking of Interfacial Hopping Diffusion

Wang, Dapeng; Wu, Haichao; Schwartz, Daniel K.

doi:10.1103/physrevlett.119.268001

Cited by 73 publications

(87 citation statements)

References 44 publications

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“…1(a)]. Further details of the technique can be found in the Supplemental Material [32]. DH PSF imaging permitted direct observations of 3D desorption-mediated hops and flights, explicitly confirming this mechanism of mass transport.…”

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confidence: 76%

“…The deviation from linearity was weakest for the repulsive FS surface (with an exponent of 0.90), and the behavior became increasingly subdiffusive for surfaces that had strong attractive interactions with HSA; the exponent decreased to 0.64 on the NH 2 -100% surfaces (Table S2 in Ref. [32]). Thus, the surface diffusion was fast and nearly Brownian for surfaces from which the macromolecule experienced electrostatic repulsion and became dramatically slower and more subdiffusive for more attractive surfaces.…”

Section: H Y S I C a L R E V I E W L E T T E R Smentioning

confidence: 99%

“…S5 of Ref. [32], this 3D MSD was dominated by in-plane motion, while the MSD in the z direction exhibited strong apparent confinement effects due to the limited axial tracking distance. Interestingly, the apparent diffusion coefficient (proportional to the slope of the MSD) depended strongly on the surface charge, with HSA diffusing most rapidly on the repulsive FS surfaces and systematically more slowly as protein-surface interactions became more attractive.…”

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confidence: 99%

“…1(a); further details are described in the Supplemental Material [32] ]. The fully 3D tracking capability allowed us to comprehensively address fundamental questions regarding macromolecular diffusion at solid-liquid interfaces.…”

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confidence: 99%

“…The repulsion was decreased and eventually changed to attraction with increasing NH 2 surface concentrations. The surface modification procedure is detailed in the Supplemental Material [32].…”

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confidence: 99%

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3D Imaging of Hopping Molecules

Barkai

Garini

2017

Physics

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Theoretical predictions have suggested that molecular motion at interfaces-which influences processes including heterogeneous catalysis, (bio)chemical sensing, lubrication and adhesion, and nanomaterial self-assembly-may be dominated by hypothetical "hops" through the adjacent liquid phase, where a diffusing molecule readsorbs after a given hop according to a probabilistic "sticking coefficient." Here, we use three-dimensional (3D) single-molecule tracking to explicitly visualize this process for human serum albumin at solid-liquid interfaces that exert varying electrostatic interactions on the biomacromolecule. Following desorption from the interface, a molecule experiences multiple unproductive surface encounters before readsorption. An average of approximately seven surface collisions is required for the repulsive surfaces, decreasing to approximately two and a half for surfaces that are more attractive. The hops themselves are also influenced by long-range interactions, with increased electrostatic repulsion causing hops of longer duration and distance. These findings explicitly demonstrate that interfacial diffusion is dominated by biased 3D Brownian motion involving bulk-surface coupling and that it can be controlled by influencing short-and long-range adsorbate-surface interactions. DOI: 10.1103/PhysRevLett.119.268001 Molecular transport in fluid phases is understood in terms of the Brownian motion of individual molecules and particles, and can, therefore, be predicted and controlled by parameters including the hydrodynamic radius and fluid viscosity. In contrast, the analogous behavior at the interfaces remains poorly understood despite its fundamental interest and technological relevance; i.e., the dynamics of macromolecules at solid-liquid interfaces underlie many applications including chemical sensing, catalysis, lubrication, and adhesion [1][2][3][4][5][6]. While interfacial diffusion is nominally two dimensional (2D) and conventionally described in terms of 2D Brownian motion, longstanding theoretical models [7][8][9][10][11][12][13][14][15][16] have predicted that interfacial mass transport could actually be dominated by "flights" through an adjacent liquid phase, which would dramatically alter the nature of interfacial molecular motion; an understanding of this process is necessary in order to rationally control mass transport at surfaces. Recent experimental results indirectly support these predictions by measuring the 2D projection of trajectories for atoms, molecules, polymers, and nanoparticles, in thin films, at solid-liquid interface, and on lipid bilayers, which can be represented as an intermittent process with periods of apparent immobility alternating with long flights comprising a heavy-tailed distribution [17][18][19][20][21][22][23][24][25][26]. However, the evidence for the presence of three-dimensional (3D) hops remains indirect, and critical aspects of the proposed "hopping" process remain a mystery. For example, theoretical models represent a flight as a series of hops (i.e., ...

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Section: H Y S I C a L R E V I E W L E T T E R Smentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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3D Imaging of Hopping Molecules

Barkai

Garini

2017

Physics

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Real‐Time Feedback‐Driven Single‐Particle Tracking: A Survey and Perspective

Heerden

Vickers

Krüger

et al. 2022

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Real‐time feedback‐driven single‐particle tracking (RT‐FD‐SPT) is a class of techniques in the field of single‐particle tracking that uses feedback control to keep a particle of interest in a detection volume. These methods provide high spatiotemporal resolution on particle dynamics and allow for concurrent spectroscopic measurements. This review article begins with a survey of existing techniques and of applications where RT‐FD‐SPT has played an important role. Each of the core components of RT‐FD‐SPT are systematically discussed in order to develop an understanding of the trade‐offs that must be made in algorithm design and to create a clear picture of the important differences, advantages, and drawbacks of existing approaches. These components are feedback tracking and control, ranging from simple proportional‐integral‐derivative control to advanced nonlinear techniques, estimation to determine particle location from the measured data, including both online and offline algorithms, and techniques for calibrating and characterizing different RT‐FD‐SPT methods. Then a collection of metrics for RT‐FD‐SPT is introduced to help guide experimentalists in selecting a method for their particular application and to help reveal where there are gaps in the techniques that represent opportunities for further development. Finally, this review is concluded with a discussion on future perspectives in the field.

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