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We evaluate critically the use of pulsed gradient spin-echo nuclear magnetic resonance (PGSE NMR) to measure molecular mobility during chemical reactions. With raw NMR spectra available in a public depository, we confirm boosted mobility during the click chemical reaction (Science 2020, 369, 537) regardless of the order of magnetic field gradient (linearly-increasing, linearly-decreasing, random sequence). We also confirm boosted mobility for the Diels-Alder chemical reaction. The conceptual advantage of the former chemical system is that constant reaction rate implies constant catalyst concentration, whereas that of the latter is the absence of a paramagnetic catalyst, precluding paramagnetism as objection to the measurements. Data and discussion in this paper show the reliability of experiments when one avoids convection, allows decay of nuclear spin magnetization between successive pulses and recovery of its intensity between gradients, and satisfies quasi-steady state during the time window to acquire each datum. Especially important is to make comparisons on the time scale of actual chemical reaction kinetics. We discuss possible sources of mistaken conclusions that are desirable to avoid., Comment: 18 pages, 4 figures

Particles kicked by external forces to produce mobility distinct from thermal diffusion are an iconic feature of the active matter problem. Here, we map this onto a minimal model for experiment and theory covering the wide time and length scales of usual active matter systems. A particle diffusing in a harmonic potential generated by an optical trap is kicked by programmed forces with time correlation at random intervals following the Poisson process. The model's generic simplicity allows us to find conditions for which displacements are Gaussian (or not), how diffusion is perturbed (or not) by kicks, and quantifying heat dissipation to maintain the non-equilibrium steady state in an active bath. The model reproduces experimental results of tracer mobility in an active bath of swimming algal cells. It can be used as a stochastic dynamic simulator for Brownian objects in various active baths without mechanistic understanding, owing to the generic framework of the protocol.

Studies of active matter, from molecular assemblies to animal groups, have revealed two broad classes of behavior: a tendency to align yields orientational order and collective motion, whereas particle repulsion leads to self-trapping and motility-induced phase separation. Here, we report a third class of behavior: orientational interactions that produce active phase separation. Combining theory and experiments on self-propelled Janus colloids, we show that stronger repulsion on the rear than on the front of these particles produces non-reciprocal torques that reorient particle motion toward high-density regions. Particles thus self-propel toward crowded areas, which leads to phase separation. Clusters remain fluid and exhibit fast particle turnover, in contrast to the jammed clusters that typically arise from self-trapping, and interfaces are sufficiently wide that they span entire clusters. Overall, our work identifies a torque-based mechanism for phase separation in active fluids, and our theory predicts that these orientational interactions yield coexisting phases that lack internal orientational order.

Molecular agitation more rapid than thermal Brownian motion is reported for cellular environments, motor proteins, synthetic molecular motors, enzymes, and common chemical reactions, yet that chemical activity couples to molecular motion contrasts with generations of accumulated knowledge about diffusion at equilibrium. To test the limits of this idea, a critical testbed is mobility of catalytically active enzymes. Sentiment is divided about reality of enhanced enzyme diffusion with evidence for and against. Here a master curve shows that enzyme diffusion coefficient increases in proportion to the energy release rate, the product of Michaelis-Menten reaction rate and Gibbs free energy change with the highly satisfactory correlation coefficient of 0.97. For ten catalytic enzymes (urease, acetylcholinesterase, seven enzymes from the glucose cascade cycle, and another), our measurements span from roughly 40% enhanced diffusion coefficient at high turnover rate and negative Gibbs free energy to no enhancement at slow turnover rate and positive Gibbs free energy. Moreover, two independent measures of mobility show consistency, provided that one avoids undesirable fluorescence photophysics. The master curve presented here quantifies the limits of both ideas, that enzymes display enhanced diffusion and that they do not within instrumental resolution, and has possible implications for understanding enzyme mobility in cellular environments. The striking linear dependence for the exergonic enzymes (negative Gibbs free energy) together with the vanishing effect for endergonic enzyme (positive Gibbs free energy) are consistent with a physical picture where the mechanism boosting the diffusion is an active one, utilizing the available work from the chemical reaction.

The solidity of glassy materials is believed to be due to the cage formed around each particle by its neighbors, but in reality the details of cage-formation remain elusive [1-4]. This cage starts to be formed at the onset temperature/density at which the normal liquid begins to show the first signs of glassy dynamics. To study cage-formation we use here focused lasers to produce a local perturbation of the structure on the particle level in 2D colloidal suspensions and monitor by means of video microscopy the system's non-linear dynamic response. All observables we probed show a response which is non-monotonic as a function of the packing fraction, peaking at the onset density. Video microscopic images reveal that this maximum response is due to the buildup of domains with cooperative dynamics that become increasingly rigid and start to dominate the particle dynamics. This proof-of-concept from microrheological deformation demonstrates that in this glass-forming liquid cage formation is directly related to the merging of these domains, thus elucidating the first step in glass-formation [1, 5]., Comment: 29 pages, 8 figures

Inspired by recent publications doubtful of the FCS technique, we scrutinize how irreversible (static) and reversible (dynamic) quenching can influence the interpretation of such data. We consider intermediate cases where the assessment of photophysics (static quenching, blinking-like triplet state relaxation) influence on autocorrelation curves can be delicate if dye-labeled objects diffuse on comparably-rapid time scales and use tryptophan as the quencher. As our example of small-molecule dye that diffuses rapidly, we mix quencher with Alexa 488 dye, and quenching is reflected in the fact that the data become exceptionally noisy. This reflects the bidisperse population of quenched and unquenched dye when the time scales overlap between the processes of translational diffusion, quenching, and blinking. As our example of large-molecule dye-labeled object, we mixed quencher with dye-labeled bovine serum albumin. Diffusion, static quenching and blinking time scales are now separated, and inferred translational diffusion now depends weakly on quencher. We conclude that when the diffusing molecule is substantially slower to diffuse than the time scale of photophysical processes of the fluorescent dye to which it is attached, influence of quenching is self-evident and the FCS autocorrelation curves give appropriate diffusion coefficient if correct fitting functions are chosen in the analysis., Comment: 11 pages, 4 figures

The concept that catalytic enzymes can act as molecular machines transducing chemical activity into motion has conceptual and experimental support, but much of the claimed support comes from experimental conditions where the substrate concentration is higher than biologically relevant and accordingly exceeds kM, the Michaelis-Menten constant. Moreover, many of the enzymes studied experimentally to date are oligomeric. Urease, a hexamer of subunits, has been considered to be the gold standard demonstrating enhanced diffusion. Here we show that urease and certain other oligomeric enzymes of high catalytic activity above kM dissociate into their smaller subunit fragments that diffuse more rapidly, thus providing a simple physical mechanism of enhanced diffusion in this regime of concentrations. Mindful that this conclusion may be controversial, our findings are sup-ported by four independent analytical techniques, static light scattering, dynamic light scattering (DLS), size-exclusion chroma-tography (SEC), and fluorescence correlation spectroscopy (FCS). Data for urease are presented in the main text and the con-clusion is validated for hexokinase and acetylcholinesterase with data presented in supplementary information. For substrate concentration regimes below kM at which these enzymes do not dissociate, our findings from both FCS and DLS validate that enzymatic catalysis does lead to the enhanced diffusion phenomenon. INTRODUCT, Comment: 7 pages, 5 figures, supplementary information

The glass is a disordered solid that processes distinct dynamical and elastic properties compared with crystal. How heterogeneous glassy materials can be and to what extent dynamics is encoded with structure and elasticity are long-standing puzzles in glass science. In this experiment, we probed the responses of binary colloidal glasses towards the excitations induced by highly focused laser pulses. We observed very similar excitation patterns when the laser was repeated in the linear region; directly proving that the dynamical heterogeneity is strongly encoded with structure. In the non-linear region, we identified a non-monotonic dynamical length scale as a function of area fraction, resulting from the non-monotonic coupling of momentum transfer in radial and orthogonal directions. Surprisingly, the excitation size and radius of gyration conformed to a universal scaling relation that covered both linear and non-linear regions. Our experiments offered a new strategy of actively probing the response of glassy materials on the microscopic level., Comment: 31 pages, 15 figures

Thermal energy agitates all matter and its competition with ordering tendencies is one of the most fundamental organizing principles in the physical world. Thus, it is natural to enquire if an effective temperature could result when external energy input enhances agitation. Potentially this could extend the insights of statistical thermodynamics to nonequilibrium systems, but despite proposals that the effective temperature concept may apply to synthetic active matter, biological motors, granular materials and turbulent fluids, its predictive value remains unclear. Here, combining computer simulations and imaging experiments, we design a two-component system of driven Janus colloids such that collisions produced by external energy sources play the role of temperature, and in this system we demonstrate quantitative agreement with hallmarks of statistical thermodynamics for binary phase behavior: the archetypal phase diagram with equilibrium critical exponents, Gaussian displacement distributions, fluctuation-dissipation relations, and capillarity. These quantitative analogies to equilibrium expectations, observed in this decidedly nonequilibrium system, constitute an existence proof from which to compare future theories of nonequilibrium, but limitations of this concept are also highlighted., Comment: Article unchanged; only corrected misspelling in author name

We present a model system in which to study natural selection in the colloid world. In the assembly of active Janus particles into rotating pinwheels when mixed with trace amounts of homogeneous colloids in the presence of an AC electric field, broken symmetry in the rotation direction produces spiral, chiral shapes. Locked into a central rotation point by the center particle, the spiral arms are found to trail rotation of the overall cluster. To achieve a steady state, the spiral arms undergo an evolutionary process to coordinate their motion. Because all the particles as segments of the pinwheel arms are self-propelled, asymmetric arm lengths are tolerated. Reconfiguration of these structures can happen in various ways and various mechanisms of this directed structural change are analyzed in detail. We introduce the concept of VIP (very important particles) to express that sustainability of active structures is most sensitive to only a few particles at strategic locations in the moving self-assembled structures.

Colloidal Janus spheres in water (one hemisphere attractive and the other repulsive) assemble into two-dimensional hexagonal crystals with orientational order controlled by anisotropic interactions. We exploit the decoupled translational and rotational order to quantify the orientational dynamics. Via imaging experiments and Monte Carlo simulations we demonstrate that the correlations in the orientation of individual Janus spheres exhibit glasslike dynamics that can be controlled via the ionic strength. Thus, these colloidal building blocks provide a particularly suitable model glass system for elucidating nontrivial dynamics arising from directional interactions, not captured by the consideration of just translational order.

We scrutinize the temporally-resolved speed of active cargo transport in living cells, and show intermittent bursting motions. These nonlinear fluctuations follow a scaling law over several decades of time and space, the statistical regularities displaying a time-averaged shape that we interpret to reflect stress buildup followed by rapid release. The power law of scaling is the same as seen in driven jammed colloids, granular, and magnetic systems. The implied regulation of active transport with environmental obstruction extends the classical notion of molecular crowding.

Single-molecule fluorescence imaging of adsorption onto initially-bare surfaces shows that polymer chains need not localize immediately after arrival. In a system optimized to present limited adsorption sites (quartz surface to which polyethylene glycol (PEG) is exposed in aqueous solution at pH = 8.2) we find that some chains diffuse back into bulk solution and re-adsorb at some distance away, sometimes multiple times before either they localize at a stable position or else diffuse away into bulk solution. This mechanism of surface diffusion is considerably more rapid than the classical model in which adsorbed polymers crawl on surfaces while the entire molecule remains adsorbed. The trajectories with jumps follow a truncated Levy distribution of step size with limiting slope -2.5, consistent with a well-defined, rapid surface diffusion coefficient over the times we observe.

We describe a simple automated method to extract and quantify transient heterogeneous dynamical changes from large datasets generated in single molecule/particle tracking experiments. Based on wavelet transform, the method transforms raw data to locally match dynamics of interest. This is accomplished using statistically adaptive universal thresholding, whose advantage is to avoid a single arbitrary threshold that might conceal individual variability across populations. How to implement this multiscale method is described, focusing on local confined diffusion separated by transient transport periods or hopping events, with 3 specific examples: in cell biology, biotechnology, and glassy colloid dynamics. This computationally-efficient method can run routinely on hundreds of millions of data points analyzed within an hour on a desktop personal computer.

We describe a straightforward, automated line tracking method to visualize within optical resolution the contour of linear macromolecules as they rearrange shape as a function of time by Brownian diffusion and under external fields such as electrophoresis. Three sequential stages of analysis underpin this method: first, "feature finding" to discriminate signal from noise; second, "line tracking" to approximate those shapes as lines; third, "temporal consistency check" to discriminate reasonable from unreasonable fitted conformations in the time domain. The automated nature of this data analysis makes it straightforward to accumulate vast quantities of data while excluding the unreliable parts of it. We implement the analysis on fluorescence images of lambda-DNA molecules in agarose gel to demonstrate its capability to produce large datasets for subsequent statistical analysis.