Enhanced Piezoelectric Response at Nanoscale Vortex Structures in Ferroelectrics
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The relative stability of reactive intermediates and reactants on a surface, which dictates the rate and selectivity of catalytic reactions in both gas and liquid phases, is dependent on numerous factors. One well-established example is secondary interactions, such as van der Waals interactions between the catalyst surface and the pendant group of the intermediate, which can govern reaction selectivity for coupling reactions. In this work, we directly show that interactions between adsorbed reaction intermediates and reactant molecules increase the binding energy and affects the geometrical arrangement of coadsorbed reactant/solvent molecules. Evidence for this effect is demonstrated for the oxidative coupling reaction of methanol on a single crystal gold (Au(110)) surface. The rate-limiting reaction intermediate for methanol selfcoupling, methoxy, stabilizes excess adsorbed methanol, which desorbs as a result of beta-hydride decomposition of the adsorbed methoxy. Direct molecular-scale imaging by scanning tunneling microscopy, supplemented by density functional theory, revealed interactive structures formed by methoxy and coadsorbed methanol. Interactions between the methoxy intermediate and coadsorbed methanol stabilizes a hydrogen-bonded network comprising methoxy and methanol by a minimum of 0.13 eV per methanol molecule. Inclusion of such interactions between reaction intermediates and coadsorbed reactants and solvents in kinetic models is important for microkinetic analysis of the rates and selectivities of catalytic reactions in both the gas and liquid phases whenever appreciable coverages of species from the ambient phase exist.
Abstract The conformational dynamics of nucleosome arrays generate a diverse spectrum of microscopic states, posing challenges to their structural determination. Leveraging cryogenic electron tomography (cryo-ET), we determine the three-dimensional (3D) structures of individual mononucleosomes and arrays comprising di-, tri-, and tetranucleosomes. By slowing the rate of condensation through a reduction in ionic strength, we probe the intra-array structural transitions that precede inter-array interactions and liquid droplet formation. Under these conditions, the arrays exhibite irregular zig-zag conformations with loose packing. Increasing the ionic strength promoted intra-array compaction, yet we do not observe the previously reported regular 30-nanometer fibers. Interestingly, the presence of H1 do not induce array compaction; instead, one-third of the arrays display nucleosomes invaded by foreign DNA, suggesting an alternative role for H1 in chromatin network construction. We also find that the crucial parameter determining the structure adopted by chromatin arrays is the angle between the entry and exit of the DNA and the corresponding tangents to the nucleosomal disc. Our results provide insights into the initial stages of intra-array compaction, a critical precursor to condensation in the regulation of chromatin organization.
A single-molecule three-dimensional (3D) structure is essential for understanding the thermal vibrations and dynamics as well as the conformational changes during the chemical reaction of macromolecules. Individual-particle electron tomography (IPET) is an approach for obtaining a snap-shot 3D structure of an individual macromolecule particle by aligning the tilt series of electron tomographic (ET) images of a targeted particle through a focused iterative 3D reconstruction method. The method can reduce the influence on the 3D reconstruction from large-scale image distortion and deformation. Due to the mechanical tilt limitation, 3D reconstruction often contains missing-wedge artifacts, presented as elongation and an anisotropic resolution. Here, we report a post-processing method to correct the missing-wedge artifact. This low-tilt tomographic reconstruction (LoTToR) method contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of ±15°. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination.
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This Perspective illustrates the growing use of ultrafast laser induced Coulomb explosion imaging methods for tracking time-evolving molecular structures and advancing understanding of gas phase molecular fragmentation processes.
The enhancement mechanism due to the molecule-surface chemical interaction in surface-enhanced Raman scattering (SERS) has been characterized using a theoretical approach based on time dependent density functional theory. This includes a systematic study of the chemical mechanism (CM) to the SERS enhancement for halogen substituted benzenethiols interacting with a silver cluster. Changing the halogen on benzenethiol enables us to systematically modulate interactions between the benzenethiol ring and the metal cluster. We observe a decrease in the CM enhancement factor with an increase in atomic number of the halogen for para- substitutions. For meta- substitutions, there is no such trend. However, the results scale linearly with the Hammett parameters for both meta and para halogens, which provides an important predictive tool for interpreting chemical enhancements. We also study the effect of solvation on the CM, showing that there is a systematic increase in enhancement with increasing solvent dielectric constant. As a result, the correlation of CM with other properties, such as the amount of charge transfer between adsorbate and metal, or the excitation energies of charge transfer states, is much less predictive than the Hammett parameter correlation.
The substrate for ribosomes actively engaged in protein synthesis is a ternary complex of elongation factor Tu (EF-Tu), aminoacyl-tRNA (aa-tRNA), and GTP. EF-Tu plays a critical role in mRNA decoding by increasing the rate and fidelity of aa-tRNA selection at each mRNA codon. Here, using three-color single-molecule fluorescence resonance energy transfer imaging and molecular dynamics simulations, we examine the timing and role of conformational events that mediate the release of aa-tRNA from EF-Tu and EF-Tu from the ribosome after GTP hydrolysis. Our investigations reveal that conformational changes in EF-Tu coordinate the rate-limiting passage of aa-tRNA through the accommodation corridor en route to the peptidyl transferase center of the large ribosomal subunit. Experiments using distinct inhibitors of the accommodation process further show that aa-tRNA must at least partially transit the accommodation corridor for EF-Tu∙GDP to release. aa-tRNAs failing to undergo peptide bond formation at the end of accommodation corridor passage after EF-Tu release can be reengaged by EF-Tu∙GTP from solution, coupled to GTP hydrolysis. These observations suggest that additional rounds of ternary complex formation can occur on the ribosome during proofreading, particularly when peptide bond formation is slow, which may serve to increase both the rate and fidelity of protein synthesis at the expense of GTP hydrolysis.
Significance It is challenging to develop biomimetic lattice self-assemblies because such materials need to resemble the flexibility and crystallinity of their biological analog. We show that these materials exhibit unique micro- and mesoscopic-ordered ultrafast hydrogen-bond dynamics, which could be a key feature in the lattice self-assembly: the ultrafast dynamics ensure flexibility, whereas the domain-level ordering reflects crystallinity. This scientific insight cannot be revealed without the ultrafast transient vibrational sum-frequency generation microscope, which integrates ultrafast interfacial spectroscopy with interfacial molecular vibrational imaging––a state-of-the-art development.
We describe a multimodal microscope for visualizing processive enzymes moving on immobilized substrates. The instrument combines interference reflection microscopy (IRM) with multi-wavelength total internal reflectance fluorescence microscopy (TIRFM). The microscope can localize quantum dots with a precision of 2.8 nm at 100 frames/s, and was used to image the dynamics of the cellulase, Cel7a interacting with surface-immobilized cellulose. The instrument, which was built with off-the-shelf components and is controlled by custom software, is suitable for tracking other degradative enzymes such as collagenases, as well as motor proteins moving along immobilized tracks.
We set ambitious goals to examine microorganism communities and measure both their chemical input and output as a read out of specific biochemical activity. These scientific goals are driving the development of sophisticated algorithms to analyze large amounts of experimental measurements made using high throughput technologies to explain and predict how the environment influences biological function at multiple scales and how the microbial systems in tum modify the environment. By examining how bacteria communities rely on symbiotic metabolic relationships for survival and reproductive success, and how these relationships consequently affect their biochemical capabilities. This was accomplished using state-of-the-art mass spectrometry-based methods, and metabolic fingerprinting approaches with a high degree of chemical specificity and sensitivity. During this period the original effort transitioned and was consolidated into what is now ENIGMA, the efforts on technology development expanded to include more untargeted metabolomics and its application to organisms on a systems level.
This project investigated physico-chemical characteristics of atmospheric particles collected during DOE ARM field campaigns and how they are involved in the hydrological cycle. Our efforts were focused on multi-modal chemical imaging and molecular characterization of atmospheric particles and snow samples collected during the Surface-Atmosphere Integrated Field Laboratory (SAIL) campaign and particle samples from the Tracking Aerosol Convection Interactions ExpeRiment (TRACER) campaign.
Coulomb explosion imaging (CEI) with x-ray free electron lasers has recently been shown to be a powerful method for obtaining detailed structural information of gas-phase planar ring molecules [R. Boll et al., X-ray multiphoton-induced Coulomb explosion images complex single molecules, Nat. Phys. 18, 423 (2022).]. In this Letter, we investigate the potential of CEI driven by a tabletop laser and extend this approach to differentiating three-dimensional structures. We study the static CEI patterns of planar and nonplanar organic molecules that resemble the structures of typical products formed in ring-opening reactions. Here, our results reveal that each molecule exhibits a well-localized and distinctive pattern in three-dimensional fragment-ion momentum space. We find that these patterns yield direct information about the molecular structures and can be qualitatively reproduced using a classical Coulomb explosion simulation. Our findings suggest that laser-induced CEI can serve as a robust method for differentiating molecular structures of organic ring and chain molecules. As such, it holds great promise as a method for following ultrafast structural changes, e.g., during ring-opening reactions, by tracking the motion of individual atoms in pump-probe experiments.
Atomic and molecular resolved atomic force microscopy (AFM) images offer unique insights into materials' properties such as local ordering, molecular orientation, and topological defects, which can be used to pinpoint physical and chemical interactions occurring at the surface. Utilizing machine learning for extracting underlying physical parameters increases the throughput of AFM data processing and eliminates inconsistencies intrinsic to manual image analysis, thus enabling the creation of reliable frameworks for qualitative and quantitative evaluation of experimental data. Here, we present a robust and scalable approach to the segmentation of AFM images based on flexible pre-selected classification criteria. The usage of supervised learning and feature extraction allows us to retain the consideration of specific problem-dependent features (such as types of periodical structures observed in the images and the associated numerical parameters: spacing, orientation, etc.). We highlight the applicability of this approach for the segmentation of molecular resolved AFM images based on the crystal orientation of the observed domains, automated selection of boundaries, and collection of relevant statistics. Finally, we outline a general strategy for machine learning-enabled analysis of nanoscale systems exhibiting periodic order that could be applied to any analytical imaging technique
Direct interspecies electron transfer (DIET) has been considered as a novel and highly efficient strategy in both natural anaerobic environments and artificial microbial fuel cells. A syntrophic model consisting of Geobacter metallireducens and Geobacter sulfurreducens was studied in this work. We conducted in vivo molecular mapping of the outer surface of the syntrophic community as the interface of nutrients and energy exchange. System for Analysis at the Liquid Vacuum Interface combined with time-of-flight secondary ion mass spectrometry was employed to capture the molecular distribution of syntrophic Geobacter communities in the living and hydrated state. Principal component analysis with selected peaks revealed that syntrophic Geobacter aggregates were well differentiated from other control samples, including syntrophic planktonic cells, pure cultured planktonic cells, and single population biofilms. Our in vivo imaging indicated that a unique molecular surface was formed. Specifically, aromatic amino acids, phosphatidylethanolamine components, and large water clusters were identified as key components that favored the DIET of syntrophic Geobacter aggregates. Moreover, the molecular changes in depths of the Geobacter aggregates were captured using dynamic depth profiling. Our findings shed new light on the interface components supporting electron transfer in syntrophic communities based on in vivo molecular imaging.
Electron cryo-tomography (cryo-ET) enables 3D imaging of complex, radiation-sensitive structures with molecular detail. However, image contrast from the interference of scattered electrons is nonlinear with atomic density and multiple scattering further complicates interpretation. These effects degrade resolution, particularly in conventional reconstruction algorithms, which assume linearity. Particle averaging can reduce such issues but is unsuitable for heterogeneous or dynamic samples ubiquitous in biology, chemistry, and materials sciences. Here, we develop a phase retrieval-based cryo-ET method, PhaseT3M. We experimentally demonstrate its application to an approximately 7 nm Co3O4 nanoparticle on an approximately 30 nm carbon substrate, achieving a maximum resolution of 1.6 Å, surpassing conventional limits using standard cryo-TEM equipment. PhaseT3M uses a multislice model for multiple scattering and Bayesian optimization for alignment and computational aberration correction, with a positivity constraint to recover ‘missing wedge’ information. Applied directly to biological particles, it enhances reconstruction quality and reduces artifacts, establishing a standard for routine 3D imaging with phase contrast.
Capturing the structural changes that molecules undergo during chemical reactions in real space and time is a long-standing dream and an essential prerequisite for understanding and ultimately controlling femtochemistry. A key approach to tackle this challenging task is Coulomb explosion imaging, which benefited decisively from recently emerging high-repetition-rate X-ray free-electron laser sources. With this technique, information on the molecular structure is inferred from the momentum distributions of the ions produced by the rapid Coulomb explosion of molecules. Retrieving molecular structures from these distributions poses a highly non-linear inverse problem that remains unsolved for molecules consisting of more than a few atoms. Here, we address this challenge using a diffusion-based Transformer neural network. We show that the network reconstructs unknown molecular geometries from ion-momentum distributions with a mean absolute error below one Bohr radius, which is half the length of a typical chemical bond.
DNA-points accumulation for imaging in nanoscale topography (DNA-PAINT) enables nanoscale imaging with virtually unlimited multiplexing and molecular counting. Here, we address challenges, such as variable imaging performance and target accessibility, that can limit its broader applicability. Specifically, we enhance its capacity for robust single-protein imaging and molecular counting by optimizing the integration of total internal reflection fluorescence microscopy with physical sectioning, in particular, Tokuyasu cryosectioning. Our method, tomographic and kinetically enhanced DNA-PAINT (tkPAINT), achieves 3 nm localization precision across diverse samples, enhanced imager binding, and improved cellular integrity. tkPAINT can facilitate molecular counting with DNA-PAINT inside the nucleus, as demonstrated through its quantification of the in situ abundance of RNA Polymerase II in both HeLa cells as well as mouse tissues. Anticipating that tkPAINT could become a versatile tool for the exploration of biomolecular organization and interactions across cells and tissues, we also demonstrate its capacity to support multiplexing, multimodal targeting of proteins and nucleic acids, and three-dimensional (3D) imaging.