Mechanism for plasmon-generated solvated electrons.

Solvated electrons are powerful reducing agents capable of driving some of the most energetically expensive reduction reactions. Their generation under mild and sustainable conditions remains challenging though. Using near-ultraviolet irradiation under low-intensity one-photon conditions coupled with electrochemical and optical detection, we show that the yield of solvated electrons in water is increased more than 10 times for nanoparticle-decorated electrodes compared to smooth silver electrodes. Based on the simulations of electric fields and hot carrier distributions, we determine that hot electrons generated by plasmons are injected into water to form solvated electrons. Both yield enhancement and hot carrier production spectrally follow the plasmonic near-field. The ability to enhance solvated electron yields in a controlled manner by tailoring nanoparticle plasmons opens up a promising strategy for exploiting solvated electrons in chemical reactions.

d-Band Hole Dynamics in Gold Nanoparticles Measured with Time-Resolved Emission Upconversion Microscopy.

The performance of photocatalysts and photovoltaic devices can be enhanced by energetic charge carriers produced from plasmon decay, and the lifetime of these energetic carriers greatly affects overall efficiencies. Although hot electron lifetimes in plasmonic gold nanoparticles have been investigated, hot hole lifetimes have not been as thoroughly studied in plasmonic systems. Here, we demonstrate time-resolved emission upconversion microscopy and use it to resolve the lifetime and energy-dependent cooling of d-band holes formed in gold nanoparticles by plasmon excitation and by following plasmon decay into interband and then intraband electron-hole pairs.

Imaging Heterogeneous 3D Dynamics of Individual Solutes in a Polyelectrolyte Brush.

Understanding molecular transport in polyelectrolyte brushes (PEBs) is crucial for applications such as separations, drug delivery, anti-fouling, and biosensors, where structural features of the polymer control intermolecular interactions. The complex structure and local heterogeneity of PEBs, while theoretically predicted, are not easily accessed with conventional experimental methods. In this work, we use 3D single-molecule tracking to understand transport behavior within a cationic poly(2-(N,N-dimethylamino)ethyl acrylate) (PDMAEA) brush using an anionic dye, Alexa Fluor 546, as the probe. The analysis is done by a parallelized, unbiased 3D tracking algorithm. Our results explicitly demonstrate that spatial heterogeneity within the brush manifests as heterogeneity of single-molecule displacements. Two distinct populations of probe motion are identified, with anticorrelated axial and lateral transport confinement, which we believe to correspond to intra- vs inter-chain probe motion.

Spectroscopic signatures of plasmon-induced charge transfer in gold nanorods.

Plasmon-induced charge transfer has been studied for the development of plasmonic photodiodes and solar cells. There are two mechanisms by which a plasmonic nanoparticle can transfer charge to an adjacent material: indirect transfer following plasmon decay and direct transfer as a way of plasmon decay. Using single-particle dark-field scattering and photoluminescence imaging and spectroscopy of gold nanorods on various substrates, we identify linewidth broadening and photoluminescence quantum yield quenching as key spectroscopic signatures that are quantitatively related to plasmon-induced interfacial charge transfer. We find that dark-field scattering linewidth broadening is due to chemical interface damping through direct charge injection via plasmon decay. The photoluminescence quantum yield quenching reveals additional mechanistic insight into electron-hole recombination as well as plasmon generation and decay within the gold nanorods. Through these two spectroscopic signatures, we identify charge transfer mechanisms at TiO2 and indium doped tin oxide interfaces and uncover material parameters contributing to plasmon-induced charge transfer efficiency, such as barrier height and resonance energy.

The competing influence of surface roughness, hydrophobicity, and electrostatics on protein dynamics on a self-assembled monolayer.

Surface morphology, in addition to hydrophobic and electrostatic effects, can alter how proteins interact with solid surfaces. Understanding the heterogeneous dynamics of protein adsorption on surfaces with varying roughness is experimentally challenging. In this work, we use single-molecule fluorescence microscopy to study the adsorption of α-lactalbumin protein on the glass substrate covered with a self-assembled monolayer (SAM) with varying surface concentrations. Two distinct interaction mechanisms are observed: localized adsorption/desorption and continuous-time random walk (CTRW). We investigate the origin of these two populations by simultaneous single-molecule imaging of substrates with both bare glass and SAM-covered regions. SAM-covered areas of substrates are found to promote CTRW, whereas glass surfaces promote localized motion. Contact angle measurements and atomic force microscopy imaging show that increasing SAM concentration results in both increasing hydrophobicity and surface roughness. These properties lead to two opposing effects: increasing hydrophobicity promotes longer protein flights, but increasing surface roughness suppresses protein dynamics resulting in shorter residence times. Our studies suggest that controlling hydrophobicity and roughness, in addition to electrostatics, as independent parameters could provide a means to tune desirable or undesirable protein interactions with surfaces.

A mechanistic examination of salting out in protein-polymer membrane interactions.

Developing a mechanistic understanding of protein dynamics and conformational changes at polymer interfaces is critical for a range of processes including industrial protein separations. Salting out is one example of a procedure that is ubiquitous in protein separations yet is optimized empirically because there is no mechanistic description of the underlying interactions that would allow predictive modeling. Here, we investigate peak narrowing in a model transferrin-nylon system under salting out conditions using a combination of single-molecule tracking and ensemble separations. Distinct surface transport modes and protein conformational changes at the negatively charged nylon interface are quantified as a function of salt concentration. Single-molecule kinetics relate macroscale improvements in chromatographic peak broadening with microscale distributions of surface interaction mechanisms such as continuous-time random walks and simple adsorption-desorption. Monte Carlo simulations underpinned by the stochastic theory of chromatography are performed using kinetic data extracted from single-molecule observations. Simulations agree with experiment, revealing a decrease in peak broadening as the salt concentration increases. The results suggest that chemical modifications to membranes that decrease the probability of surface random walks could reduce peak broadening in full-scale protein separations. More broadly, this work represents a proof of concept for combining single-molecule experiments and a mechanistic theory to improve costly and time-consuming empirical methods of optimization.

Single-Molecule Dynamics Reflect IgG Conformational Changes Associated with Ion-Exchange Chromatography.

Conformational changes of antibodies and other biologics can decrease the effectiveness of pharmaceutical separations. Hence, a detailed mechanistic picture of antibody-stationary phase interactions that occur during ion-exchange chromatography (IEX) can provide critical insights. This work examines antibody conformational changes and how they perturb antibody motion and affect ensemble elution profiles. We combine IEX, three-dimensional single-protein tracking, and circular dichroism spectroscopy to investigate conformational changes of a model antibody, immunoglobulin G (IgG), as it interacts with the stationary phase as a function of salt conditions. The results indicate that the absence of salt enhances electrostatic attraction between IgG and the stationary phase, promotes surface-induced unfolding, slows IgG motion, and decreases elution from the column. Our results reveal previously unreported details of antibody structural changes and their influence on macroscale elution profiles.

A new metric for relating macroscopic chromatograms to microscopic surface dynamics: the distribution function ratio (DFR).

Heterogeneous stationary phase chemistry causes chromatographic tailing that lowers separation efficiency and complicates optimizing mobile phase conditions. Model-free metrics are attractive for assessing optimal separation conditions due to the low quantity of information required, but often do not reveal underlying mechanisms that cause tailing, for example, heterogeneous retention modes. We report a new metric, which we call the Distribution Function Ratio (DFR), based on a graphical comparison between the chromatogram and Gaussian cumulative distribution functions, achieving correspondence to ground truth surface dynamics with a single chromatogram. Using a Monte Carlo framework, we show that the DFR can predict the prevalence of heterogeneous retention modes with high precision when the relative desorption rate between modes is known, as in during surface dynamics experiments. Ground truth comparisons reveal that the DFR outperforms both the asymmetry factor and skewness by yielding a one-to-one correspondence with heterogeneous retention mode prevalence over a broad range of experimentally realistic values. Perhaps of more value, we illustrate that the DFR, when combined with the asymmetry factor and skewness, can estimate microscopic surface dynamics, providing valuable insights into surface chemistry using existing chromatographic instrumentation. Connecting ensemble results to microscopic quantities through the lens of simulation establishes a new chemistry-driven route to measuring and advancing separations.

Untying the Gordian KNOT: Unbiased Single Particle Tracking Using Point Clouds and Adaptive Motion Analysis.

Achieving mechanistic understanding of transport in complex environments such as inside cells or at polymer interfaces is challenging. We need better ways to image transport in 3-D and better single particle tracking algorithms to determine transport that are not systemically biased toward any classical motion model. Here we present an unbiased single particle tracking algorithm: Knowing Nothing Outside Tracking (KNOT). KNOT uses point clouds provided by iterative deconvolution to educate individual particle localizations and link particle positions between frames to achieve 2-D and 3-D tracking. Information from prior point clouds fuels an independent adaptive motion model for each particle to avoid global models that could introduce biases. KNOT competes with or surpasses other 2-D methods from the 2012 particle tracking challenge while accurately tracking adsorption dynamics of proteins on polymer surfaces and early endosome transport in live cells in 3-D. We apply KNOT to study 3-D endosome transport to reveal new physical insight into locally directed and diffusive transport in live cells. Our analysis demonstrates better accuracy in classifying local motion and its direction compared to previous methods, revealing intricate intracellular transport heterogeneities.

Transforming Separation Science with Single-Molecule Methods.

Empirical optimization of the multiscale parameters underlying chromatographic and membrane separations leads to enormous resource waste and production costs. A bottom-up approach to understand the physical phenomena underlying challenges in separations is possible with single-molecule observations of solute-stationary phase interactions. We outline single-molecule fluorescence techniques that can identify key interactions under ambient conditions. Next, we describe how studying increasingly complex samples heightens the relevance of single-molecule results to industrial applications. Finally, we illustrate how separation methods that have not been studied at the single-molecule scale can be advanced, using chiral chromatography as an example case. We hope new research directions based on a molecular approach to separations will emerge based on the ideas, technologies, and open scientific questions presented in this Perspective.

Polymer Free Volume Effects on Protein Dynamics in Polystyrene Revealed by Single-Molecule Spectroscopy.

Protein-polymer interactions are critical to applications ranging from biomedical devices to chromatographic separations. The mechanistic relationship between the microstructure of polymer chains and protein interactions is challenging to quantify and not well studied. Here, single-molecule microscopy is used to compare the dynamics of two model proteins, α-lactalbumin and lysozyme, at the interface of uncharged polystyrene with varied molecular weights. The two proteins exhibit different surface interaction mechanisms despite having a similar size and structure. α-Lactalbumin exhibits interfacial adsorption-desorption with residence times that depend on polymer molecular weight. Lysozyme undergoes a continuous time random walk at the polystyrene surface with residence times that also depend on the molecular weight of polystyrene. Single-molecule observables suggest that the hindered continuous time random walk dynamics displayed by lysozyme are determined by the polystyrene free volume, a finding supported by thermal annealing and solvent quality studies. Hindered dynamics are dominated by short-range hydrophobic interactions where the contributions of electrostatic forces are negligible. This work establishes a relationship between the microscale structure (i.e., free volume) of polystyrene polymer chains to nanoscale interfacial protein dynamics.

Quantitative Analysis of Nanorod Aggregation and Morphology from Scanning Electron Micrographs Using SEMseg.

General methods to achieve better physical insight about nanoparticle aggregation and assembly are needed because of the potential role of aggregation in a wide range of materials, environmental, and biological outcomes. Scanning electron microscopy (SEM) is fast and affordable compared to transmission electron microscopy, but SEM micrographs lack contrast and resolution due to lower beam energy, topographic contrast, edge effects, and charging. We present a new segmentation algorithm called SEMseg that is robust to the challenges inherent in SEM micrograph analysis and demonstrate its utility for analyzing gold (Au) nanorod aggregates. SEMseg not only supports nanoparticle size analysis for dispersed nanoparticles, but also discriminates between nanoparticles within an aggregate. We compare our algorithm to those incorporated into the commonly used software ImageJ and demonstrate improved segmentation of aggregate structures. New physical insight about aggregation is demonstrated by the introduction of an order parameter describing side-by-side structure in nanoparticle aggregates. We also present the segmentation and fitting algorithms included in SEMseg within a user-friendly graphical user interface. The resulting code is provided with an open-source interface to provide quantitative image processing tools for researchers to characterize both dispersed nanoparticles and nanoparticle assemblies in SEM micrographs with high throughput.

Acoustic Vibrations of Al Nanocrystals: Size, Shape, and Crystallinity Revealed by Single-Particle Transient Extinction Spectroscopy.

Acoustic vibrations in plasmonic nanoparticles, monitored by an all-optical means, have attracted significant increasing interest because they provide unique insight into the mechanical properties of these metallic nanostructures. Al nanostructures are a recently emerging alternative to noble metal nanoparticles, because their broad wavelength tunability and high natural abundance make them ideal for many potential applications. Here, we investigate the acoustic vibrations of individual Al nanocrystals using a combination of electron microscopy and single-particle transient extinction spectroscopy, made possible with a low-pulse energy, high sensitivity, and probe-wavelength-tunable, single-particle transient extinction microscope. For chemically synthesized, faceted Al nanocrystals, the observed vibration frequency scales with the inverse particle diameter. In contrast, triangularly shaped Al nanocrystals support two distinct frequencies, corresponding to their in- and out-of-plane breathing modes. Unlike ensemble measurements, which measure average properties, measuring the damping time of the acoustic vibrations for individual particles enables us to investigate variations of the quality factor on the particle-to-particle level. Surprisingly, we find a large variation in quality factors even for nanocrystals of similar size and shape. This observed heterogeneity appears to result from substantially varying degrees of nanoparticle crystallinity even for chemically synthesized nanocrystals.

Hot Holes Assist Plasmonic Nanoelectrode Dissolution.

Strong light-absorbing properties allow plasmonic metal nanoparticles to serve as antennas for other catalysts to function as photocatalysts. To achieve plasmonic photocatalysis, the hot charge carriers created when light is absorbed must be harnessed before they decay through internal relaxation pathways. We demonstrate the role of photogenerated hot holes in the oxidative dissolution of individual gold nanorods with millisecond time resolution while tuning charge-carrier density and photon energy using snapshot hyperspectral imaging. We show that light-induced hot charge carriers enhance the rate of gold oxidation and subsequent electrodissolution. Importantly, we distinguish how hot holes generated from interband transitions versus hot holes around the Fermi level contribute to photooxidative dissolution. The results provide new insights into hot-hole-driven processes with relevance to photocatalysis while emphasizing the need for statistical descriptions of nonequilibrium processes on innately heterogeneous nanoparticle supports.

From a Protein's Perspective: Elution at the Single-Molecule Level.

Column chromatography is a widely used analytical technique capable of identifying and isolating a desired chemical species from a more complicated mixture. Despite the method's prevalence, theoretical descriptions have not advanced to accommodate today's common analyte, proteins. Proteins are increasingly used as biologics, a term that refers to biological pharmaceuticals, and present new complexities for chromatographic separation. Large variations in surface charge, chemistry, and structure among protein analytes expose the limits in the current theoretical framework's ability to predict the efficiency of a column without empirical data. The bottleneck created by empirical optimization is a strong motivation for a renewed effort to achieve an in-depth understanding of the range of interactions that occur between a protein analyte and the stationary phase that together enable its selective separation from other constituents of a mixture. The physical and chemical processes that dictate the amount of time an analyte spends in the column are often abstracted by theory and treated as statistical distributions. Until recently, these distributions could not be mapped experimentally as traditional experimental techniques could not reveal underlying heterogeneity in structure, charge, and dynamics. Aligning the latest experimental and theoretical advances is thus a hurdle to be overcome so that significant progress can be made toward a predictive chromatographic theory. In this Account, we detail the work of the Landes Lab in developing single-molecule techniques that refine the stochastic theory of chromatography as a first step toward predictive chromatographic column design. We provide a brief review of the development of stochastic theory and establish a mathematical framework to put the discussed physical chemistry in context. We describe our investigations of three pertinent phenomena: mobile/stationary phase exchange, adsorption/desorption kinetics, and hindered diffusion. We highlight experimental evidence that points to nonuniform behavior. Then, we describe our work in developing single-molecule techniques that can evaluate these effects on a protein-by-protein basis. We highlight two developments: fast imaging via super temporal-resolved microscopy (STReM) and visualizing diffusion within pores via a combination of fluorescence correlation spectroscopy and super-resolution optical fluctuation imaging (fcsSOFI). Both methods offer new ways to study chromatographic elution at the single-protein level. Such methods can identify the rare heterogeneities that prevent efficient separations and advance the field closer to predictively optimized protein separations.

Generalized method to design phase masks for 3D super-resolution microscopy.

Point spread function (PSF) engineering by phase modulation is a novel approach to three-dimensional (3D) super-resolution microscopy, with different point spread functions being proposed for specific applications. It is often not easy to achieve the desired shape of engineered point spread functions because it is challenging to determine the correct phase mask. Additionally, a phase mask can either encode 3D space information or additional time information, but not both simultaneously. A robust algorithm for recovering a phase mask to generate arbitrary point spread functions is needed. In this work, a generalized phase mask design method is introduced by performing an optimization. A stochastic gradient descent algorithm and a Gauss-Newton algorithm are developed and compared for their ability to recover the phase masks for previously reported point spread functions. The new Gauss-Newton algorithm converges to a minimum at much higher speeds. This algorithm is used to design a novel stretching-lobe phase mask to encode temporal and 3D spatial information simultaneously. The stretching-lobe phase mask and other masks are fabricated in-house for proof-of-concept using multi-level light lithography and an optimized commercially sourced stretching-lobe phase mask (PM) is validated experimentally to encode 3D spatial and temporal information. The algorithms' generalizability is further demonstrated by generating a phase mask that comprises four different letters at different depths.

Enhancing Analytical Separations Using Super-Resolution Microscopy.

Super-resolution microscopy is becoming an invaluable tool to investigate structure and dynamics driving protein interactions at interfaces. In this review, we highlight the applications of super-resolution microscopy for quantifying the physics and chemistry that occur between target proteins and stationary-phase supports during chromatographic separations. Our discussion concentrates on the newfound ability of super-resolved single-protein spectroscopy to inform theoretical parameters via quantification of adsorption-desorption dynamics, protein unfolding, and nanoconfined transport.

The structure-energy landscape of NMDA receptor gating.

N-Methyl-D-aspartate (NMDA) receptors are the main calcium-permeable excitatory receptors in the mammalian central nervous system. The NMDA receptor gating is complex, exhibiting multiple closed, open, and desensitized states; however, central questions regarding the conformations and energetics of the transmembrane domains as they relate to the gating states are still unanswered. Here, using single-molecule Förster resonance energy transfer (smFRET), we map the energy landscape of the first transmembrane segment of the Rattus norvegicus NMDA receptor under resting and various liganded conditions. These results show kinetically and structurally distinct changes associated with apo, agonist-bound, and inhibited receptors linked by a linear mechanism of gating at this site. Furthermore, the smFRET data suggest that allosteric inhibition by zinc occurs by an uncoupling of the agonist-induced changes at the extracellular domains from the gating motions leading to an apo-like state, while dizocilpine, a pore blocker, stabilizes multiple closely packed transmembrane states.

Single Particle Tracking: From Theory to Biophysical Applications.

After three decades of developments, single particle tracking (SPT) has become a powerful tool to interrogate dynamics in a range of materials including live cells and novel catalytic supports because of its ability to reveal dynamics in the structure-function relationships underlying the heterogeneous nature of such systems. In this review, we summarize the algorithms behind, and practical applications of, SPT. We first cover the theoretical background including particle identification, localization, and trajectory reconstruction. General instrumentation and recent developments to achieve two- and three-dimensional subdiffraction localization and SPT are discussed. We then highlight some applications of SPT to study various biological and synthetic materials systems. Finally, we provide our perspective regarding several directions for future advancements in the theory and application of SPT.

Nanoelectrode-emitter spectral overlap amplifies surface enhanced electrogenerated chemiluminescence.

Electrogenerated chemiluminescence (ECL) is a promising technique for low concentration molecular detection. To improve the detection limit, plasmonic nanoparticles have been proposed as signal boosting antennas to amplify ECL. Previous ensemble studies have hinted that spectral overlap between the nanoparticle antenna and the ECL emitter may play a role in signal enhancement. Ensemble spectroscopy, however, cannot resolve heterogeneities arising from colloidal nanoparticle size and shape distributions, leading to an incomplete picture of the impact of spectral overlap. Here, we isolate the effect of nanoparticle-emitter spectral overlap for a model ECL system, coreaction of tris(2,2'-bipyridyl)dichlororuthenium(ii) hexahydrate and tripropylamine, at the single-particle level while minimizing other factors influencing ECL intensities. We found a 10-fold enhancement of ECL among 952 gold nanoparticles. This signal enhancement is attributed exclusively to spectral overlap between the nanoparticle and the emitter. Our study provides new mechanistic insight into plasmonic enhancement of ECL, creating opportunities for low concentration ECL sensing.