Experimental Guidelines to Image Transient Single-Molecule Events Using Graphene Liquid Cell Electron Microscopy

Nanopipette dynamic microscopy unveils nano coffee ring

Liquid-phase electron microscopy (LP-EM) imaging has revolutionized our understanding of nanosynthesis and assembly. However, the current closed geometry limits its application for open systems. The ubiquitous physical process of the coffee-ring phenomenon that underpins materials and engineering science remains elusive at the nanoscale due to the lack of experimental tools. We introduce a quartz nanopipette liquid cell with a tunable dimension that requires only standard microscopes. Depending on the imaging condition, the open geometry of the nanopipette allows the imaging of evaporation-induced pattern formation, but it can also function as an ordinary closed-geometry liquid cell where evaporation is negligible despite the nano opening. The nano coffee-ring phenomenon was observed by tracking individual nanoparticles in an evaporating nanodroplet created from a thin liquid film by interfacial instability. Nanoflows drive the assembly and disruption of a ring pattern with the absence of particle-particle correlations. With surface effects, nanoflows override thermal fluctuations at tens of nanometers, in which nanoparticles displayed a "drunken man trajectory" and performed work at a value much smaller than kBT.

Modes of Nanodroplet Formation and Growth on an Ultrathin Water Film

Using nanobubbles as geometrical confinements, we create a thin water film (∼10 nm) in a graphene liquid cell and investigate the evolution of its instability at the nanoscale under transmission electron microscopy. The breakdown of the water films, resulting in the subsequent formation and growth of nanodroplets, is visualized and generalized into different modes. We identified distinct droplet formation and growth modes by analyzing the dynamic processes involving 61 droplets and 110 liquid bridges within 31 Graphene Liquid Cells (GLCs). Droplet formation is influenced by their positions in GLCs, taking on a semicircular shape at the edge and a circular shape in the middle. Growth modes include liquid mass transfer driven by Plateau-Rayleigh instability and merging processes in and out-of-plane of the graphene interface. Droplet growth can lead to the formation of liquid bridges for which we obtain multiview projections. Data analysis reveals the general dynamics of liquid bridges, including drawing liquids from neighboring residual water films, merging with surrounding droplets, and merging with other liquid bridges. Our experimental observations provide insights into fluid transport at the nanoscale.

Revealing microscopic dynamics: in situ liquid-phase TEM for live observations of soft materials and quantitative analysis via deep learning

In various domains spanning materials synthesis, chemical catalysis, life sciences, and energy materials, in situ transmission electron microscopy (TEM) methods exert a profound influence. These methodologies enable the real-time observation and manipulation of gas-phase and liquid-phase reactions at the nanoscale, facilitating the exploration of pivotal reaction mechanisms. Fundamental research areas like crystal nucleation, growth, etching, and self-assembly have greatly benefited from these techniques. Additionally, their applications extend across diverse fields such as catalysis, batteries, bioimaging, and drug delivery kinetics. However, the intricate nature of 'soft matter' presents a challenge due to the unique molecular properties and dynamic behavior of these substances that remain insufficiently understood. Investigating soft matter within in situ liquid-phase TEM settings demands further exploration and advancement compared to other research domains. This research harnesses the potential of in situ liquid-phase TEM technology while integrating deep learning methodologies to comprehensively analyze the quantitative aspects of soft matter dynamics. This study centers on diverse phenomena, encompassing surfactant molecule nucleation, block copolymer behavior, confinement-driven self-assembly, and drying processes. Furthermore, deep learning techniques are employed to precisely analyze Ostwald ripening and digestive ripening dynamics. The outcomes of this study not only deepen the understanding of soft matter at its fundamental level but also serve as a pivotal foundation for developing innovative functional materials and cutting-edge devices.

Single-Molecule Graphene Liquid Cell Electron Microscopy for Instability of Intermediate Amyloid Fibrils

Single-molecule techniques are powerful microscopy methods that provide new insights into biological processes. Liquid-phase transmission electron microscopy (LP-TEM) is an ideal single-molecule technique for overcoming the poor spatiotemporal resolution of optical approaches. However, single-molecule LP-TEM is limited by several challenges such as electron-beam-induced molecular damage, difficulty in identifying biomolecular species, and a lack of analytical approaches for conformational dynamics. Herein, a single-molecule graphene liquid-cell TEM (GLC-TEM) technique that enables the investigation of real-time structural perturbations of intact amyloid fibrils is presented. It is demonstrated that graphene membranes significantly extend the observation period of native amyloid beta proteins without causing oxidative damage owing to electron beams, which is necessary for imaging. Stochastic and time-resolved investigations of single fibrils reveal that structural perturbations in the early fibrillar stage are responsible for the formation of various amyloid polymorphs. The advantage of observing structural behavior in real time with unprecedented resolution will potentially make GLC-TEM a complementary approach to other single-molecule techniques.

The ergodicity question when imaging DNA conformation using liquid cell electron microscopy

Assessing the ergodicity of graphene liquid cell electron microscope measurements, we report that loop states of circular DNA interconvert reversibly and that loop numbers follow the Boltzmann distribution expected for this molecule in bulk solution, provided that the electron dose is low (80-keV electron energy and electron dose rate 1-20 e- Å-2 s-1). This imaging technique appears to act as a "slow motion" camera that reveals equilibrated distributions by imaging the time average of a few molecules without the need to image a spatial ensemble.

High-Resolution Electron Diffraction of Hydrated Protein Crystals at Room Temperature

Structural characterization is crucial to understanding protein function. Compared with X-ray diffraction methods, electron crystallography can be performed on nanometer-sized crystals and can provide additional information from the resulting Coulomb potential map. Whereas electron crystallography has successfully resolved three-dimensional structures of vitrified protein crystals, its widespread use as a structural biology tool has been limited. One main reason is the fragility of such crystals. Protein crystals can be easily damaged by mechanical stress, change in temperature, or buffer conditions as well as by electron irradiation. This work demonstrates a methodology to preserve these nanocrystals in their natural environment at room temperature for electron diffraction experiments as an alternative to existing cryogenic techniques. Lysozyme crystals in their crystallization solution are hermetically sealed via graphene-coated grids, and their radiation damage is minimized by employing a low-dose data collection strategy in combination with a hybrid-pixel direct electron detector. Diffraction patterns with reflections of up to 3 Å are obtained and successfully indexed using a template-matching algorithm. These results demonstrate the feasibility of in situ protein electron diffraction. The method described will also be applicable to structural studies of hydrated nanocrystals important in many research and technological developments.

Visualizing the multi-level assembly structures of conjugated molecular systems with chain-length dependent behavior

It remains challenging to understand the structural evolution of conjugated polymers from single chains to solvated aggregates and film microstructures, although it underpins the performance of optoelectrical devices fabricated via the mainstream solution processing method. With several ensemble visual measurements, here we unravel the morphological evolution process of a model system of isoindigo-based conjugated molecules, including the hidden molecular assembly pathways, the mesoscale network formation, and their unorthodox chain dependence. Short chains show rigid chain conformations forming discrete aggregates in solution, which further grow to form a highly ordered film that exhibits poor electrical performance. In contrast, long chains exhibit flexible chain conformations, creating interlinked aggregates networks in solution, which are directly imprinted into films, forming interconnective solid-state microstructure with excellent electrical performance. Visualizing multi-level assembly structures of conjugated molecules provides a deep understanding of the inheritance of assemblies from solution to solid-state, accelerating the optimization of device fabrication.

Deep learning-assisted analysis of single molecule dynamics from liquid-phase electron microscopy

We apply U-Net and UNet++ to analyze single-molecule movies obtained from liquid-phase electron microscopy. Neural networks allow full automation, and high throughput analysis of these low signal-to-noise ratio images, while achieving higher segmentation accuracy, and avoiding subjective errors as compared to the conventional threshold methods. The analysis enables the quantification of transient dynamics in chemical systems and the capture of rare intermediate states by resolving local conformational changes within a single molecule.