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At least 73 records · Page 4

Janus skyrmion: Interfacial quasiparticle with two-faced helicity

Janus particles are functional particles with at least two surfaces showing asymmetric properties. Here, we show at the interface between two magnetic regions with different antisymmetric exchange interactions, an alternative species of two-dimensional topological quasiparticles can emerge, in which different helicity structures can coexist. We name such an interfacial quasiparticle a “Janus skyrmion,” in analogy to the Janus particle. As the Janus skyrmion shows helicity asymmetry, its size could vary with both the in-plane and out-of-plane magnetic fields. A vertical spin current could drive the Janus skyrmion into one-dimensional motion along the interface without showing the skyrmion Hall effect, at a speed which depends on both the in-plane spin-polarization direction and current density. Thermal fluctuations could also lead to one-dimensional random walk of a Brownian Janus skyrmion. This work uncovers unique dynamics intrinsic to interfacial quasiparticles with exotic helicity, which may be realized in interface-engineered magnetic layers.

36 MATERIALS SCIENCE↗

Stochastic exciton-scattering theory of optical line shapes: Renormalized many-body contributions

Spectral line shapes provide a window into the local environment coupled to a quantum transition in the condensed phase. In this paper, we build upon a stochastic model to account for non-stationary background processes produced by broad-band pulsed laser stimulation, as distinguished from those for stationary phonon bath. In particular, we consider the contribution of pair-fluctuations arising from the full bosonic many-body Hamiltonian within a mean-field approximation, treating the coupling to the system as a stochastic noise term. Herein, using the Itô transformation, we consider two limiting cases for our model, which lead to a connection between the observed spectral fluctuations and the spectral density of the environment. In the first case, we consider a Brownian environment and show that this produces spectral dynamics that relax to form dressed excitonic states and recover an Anderson–Kubo-like form for the spectral correlations. In the second case, we assume that the spectrum is Anderson–Kubo like and invert to determine the corresponding background. Using the Jensen inequality, we obtain an upper limit for the spectral density for the background. The results presented here provide the technical tools for applying the stochastic model to a broad range of problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning-driven descriptions of protein dynamics at solid-liquid interfaces

This chapter has described how ML has enabled quantitative analysis of HS-AFM data to discover the physical phenomena governing protein dynamics and ordering at solid-liquid interfaces. The research detailed in this chapter modeled the rotation models of protein nanorods, the discovery of which would otherwise not be possible. By tracking the trajectories of individual protein rods from frame to frame, it was possible to model Brownian type motion and behaviors and Levy-flight dynamics that had not previously been shown. We also described the application of the Python package AtomAI, which has been developed specifically to analyze and extract physical phenomena, providing exemplar code for training an ensemble of deep neural networks to produce the semantic segmentation of AFM data and functions for encoding and decoding local environments. We last described a combinatorial approach to analyze very noisy data with a densely covered substrate where the emergence of order for the protein liquid crystals could be elucidated. By combining the methods from Case 1 and 2, it was possible to obtain the center of mass and angle for each rod in the images and track the assembly of the rods over time into a 2D liquid crystal array on the surface of mica.

protein dynamics, solid-liquid interfaces, atomic ↗

Intermediate scattering functions of a rigid body monoclonal antibody protein in solution studied by dissipative particle dynamic simulation

In the past decade, there was increased research interest in studying internal motions of flexible proteins in solution using Neutron Spin Echo (NSE) as NSE can simultaneously probe the dynamics at the length and time scales comparable to protein domain motions. However, the collective intermediate scattering function (ISF) measured by NSE has the contributions from translational, rotational, and internal motions, which are rather complicated to be separated. Widely used NSE theories to interpret experimental data usually assume that the translational and rotational motions of a rigid particle are decoupled and independent to each other. To evaluate the accuracy of this approximation for monoclonal antibody (mAb) proteins in solution, dissipative particle dynamic computer simulation is used here to simulate a rigid-body mAb for up to about 200 ns. The total ISF together with the ISFs due to only the translational and rotational motions as well as their corresponding effective diffusion coefficients is calculated. The aforementioned approximation introduces appreciable errors to the calculated effective diffusion coefficients and the ISFs. For the effective diffusion coefficient, the error introduced by this approximation can be as large as about 10% even though the overall agreement is considered reasonable. Thus, we need to be cautious when interpreting the data with a small signal change. In addition, the accuracy of the calculated ISFs due to the finite computer simulation time is also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Statistical Learning for Nonlinear Model Reduction from Local Simulations of Stochastic and Particle- and Agent-Based Systems

Stochastic physical systems across the sciences that have very high-dimensional state spaces, with a large number of fast degrees of freedom that force direct simulators to proceed by integration steps that are orders of magnitude smaller than events of interests (e.g., particle collisions). Examples range from molecular motion to dynamics of large populations of cells. A grand challenge in the simulation and understanding of such systems is the systematic construction of accurate, interpretable, reduced models, enabling faster simulations, revealing fundamental properties of the dynamics, and predicting phenomena of interest that the original simulator could not reached with sufficient accuracy or within a given computational budget. In this projected we developed novel statistical estimation/machine learning techniques for analyzing and building empirical reduced models for important families of high-dimensional stochastic systems, in particular: - we developed techniques for estimating interaction kernels in interacting particle- and agent-based systems, which are ubiquitous in Physics, Biology and many other sciences, given observed trajectories of the system; - we developed techniques for nonlinear model reduction for high-dimensional stochastic systems that have a small number of unknown, nonlinear slow variables, and a large number of fast modes, that are possibly of large magnitude, given observed short trajectories of the system in the form of bursts of trajectories from different initial conditions; - we developed novel techniques for estimating linear dynamical systems on graphs when both the dynamics and the underlying graph are unknown, and we have a sparse set of space-time observations; - we considered the problem of estimating an unknown nonlinear observation function of a standard process (e.g. Brownian motion), so that we can recognized if an observed dynamics is "just" a nonlinear version of a known dynamics; we also developed benchmarks for learning algorithms aimed at learning and classifying diffusion processes.

97 MATHEMATICS AND COMPUTING↗

Defect Self-Elimination in Nanocube Superlattices Through the Interplay of Brownian, van der Waals, and Ligand-Based Forces and Torques

Understanding defect healing is necessary for realizing devices based on nanoparticle-superlattices with controlled electronic and optoelectronic performance. However, key questions remain regarding nanoparticle interactions and resulting assembly dynamics and defect self-elimination. In particular, for anisotropic particles, additional degrees of freedom beyond those of spherical particles, such as rotational dynamics and toques, significantly impact phenomena. Here, in this work, we investigate nanocube (NC) superlattices by employing liquid phase transmission electron microscopy, continuum theories and molecular dynamics simulations. Analyzing interparticle forces and torques due to van der Waals, Brownian, and ligand interactions, we find that the latter dominates and that the anisotropic NC morphology introduces significant torques. In imperfect regions, unbalanced forces and torques induce NC translations and rotations that are transmitted to neighboring NCs, prompting “chain interactions” in a 2D network, which lead to defect self-elimination. This fundamental understanding will further enable design and fabrication of defect-free superlattices, as well as those with tailored defects, via assembly of anisotropic particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model-Free Measurement of Local Entropy Production and Extractable Work in Active Matter

Time-reversal symmetry breaking and entropy production are universal features of nonequilibrium phenomena. Despite its importance in the physics of active and living systems, the entropy production of systems with many degrees of freedom has remained of little practical significance because the high dimensionality of their state space makes it difficult to measure. Here, in this work, we introduce a local measure of entropy production and a numerical protocol to estimate it. We establish a connection between the entropy production and extractability of work in a given region of the system and show how this quantity depends crucially on the degrees of freedom being tracked. We validate our approach in theory, simulation, and experiments by considering systems of active Brownian particles undergoing motility-induced phase separation, as well as active Brownian particles and E.coli in a rectifying device in which the time-reversal asymmetry of the particle dynamics couples to spatial asymmetry to reveal its effects on a macroscopic scale.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Diffusion-mediated passing of molecular species in linear nanopores constrained by orientational alignment

For diffusion-mediated catalytic conversion reactions in materials with narrow linear nanopores, e.g., mesoporous silica MCM-41, a key parameter is the propensity for product species to be able to pass reactant species and thus to efficiently exit the pore. For elongated species, this can require orientational alignment with the pore axis. In this work, we perform benchmark analyses for such solution-phase systems where one of these species is elongated in order to quantify the dependence of this passing propensity, P, on pore diameter and on the rotational diffusion coefficient, Dr, of the elongated species. In particular, we consider the passing of a spherical and an elongated spherocylindrical shaped species in a cylindrical pore in an implicit solvent, where these species cannot overlap. Passing is mediated by diffusive Brownian motion of these species as described by strongly damped Langevin dynamics. We quantify scaling of P for pore width just above the threshold where passing is sterically blocked, and also reveal a significant decrease in P for lower Dr. We also consider the dependence of P on the aspect ratio of the elongated species and obtain an exact result in the limiting regime of large aspect ratio.

Brownian motion↗

Diffusion characteristics of water molecules in a lamellar structure formed by triblock copolymers

The distribution and diffusion of water molecules are playing important roles in determining self-assembly and transport properties of polymeric systems. Small-angle neutron scattering (SANS) experiments and molecular dynamics (MD) simulation have been applied to understand the distribution of water molecules and their dynamics in the lamellar membrane formed by Pluronic L62 block copolymers. Penetration of water molecules into the polyethylene oxide (PEO) layers of the membranes has been estimated using scattering length density (SLD) profiles obtained from SANS measurements, which agree well with the molecular distribution observed from MD simulations. The water diffusion coefficient at different regions of the lamellar membrane was further investigated using MD simulation. The diffusion characteristic shows a transition from normal to anomalous diffusion as the position of the water molecule changes from the bulk to PEO and to the polypropylene oxide (PPO) layer. Here we find that water molecules within the PEO or PPO layers follow subdiffusive dynamics, which can be interpreted by the model of fractional Brownian motion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developments in SRW Code and Sirepo Framework Supporting Simulation of Time-Dependent Coherent X-ray Scattering Experiments

Physical optics simulations for beamlines and experiments are essential for the effective use of synchrotron light source facilities such as NSLS-II at BNL. The SRW software package supports such source-to-detector simulations for coherent X-ray scattering and imaging experiments through its Python interface and Sirepo browser-based graphical user interface. This allows one to define custom sample models, assess the feasibility of an experiment, and estimate most appropriate beamline settings before using valuable beamtime. We discuss the recent use of general-purpose GPU resources and coherent mode decomposition algorithms in SRW to accelerate physical optics simulations with partially coherent X-rays. To illustrate these new capabilities, we describe simulations of typical time series of partially coherent scattering images used in X-ray Photon Correlation Spectroscopy (XPCS) experiments; aiming to characterize the nanoscale dynamics of a disordered sample, representing a solution of nanoparticles undergoing Brownian diffusion.

36 MATERIALS SCIENCE↗

Unifying disparate rate-dependent rheological regimes in non-Brownian suspensions

A typical dense non-Brownian particulate suspension exhibits shear thinning (decreasing viscosity) at low shear rate/stress followed by a Newtonian plateau (constant viscosity) at intermediate shear rate/stress values which transitions to shear thickening (increasing viscosity) beyond a critical shear rate/stress value and finally, undergoes a second shear thinning transition at extremely high shear rate/stress values. In this study, we unify and quantitatively reproduce all the disparate rate dependent regimes and the corresponding transitions for a dense non-Brownian suspension with increasing shear rate/stress. Here, we employ discrete particle dynamics simulations based on the proposed mechanism to elucidate its accuracy. We find that a competition between inter-particle interactions of hydrodynamic and non-hydrodynamic origins and the switching in the dominant stress scale with increasing the shear rate/stress lead to each of the above transitions. Inclusion of traditional hydrodynamic interactions, attractive/repulsive DLVO (Derjaguin and Landau, Verwey and Overbeek) interactions, the inter-particle contact interactions and a constant friction (or other constraint mechanism) reproduce the initial thinning as well as the shear thickening transition. However, to quantitatively capture the intermediate Newtonian plateau and the second shear thinning, an additional non-hydrodynamic interaction of non-DLVO origin and a decreasing coefficient of friction, respectively, are essential; thus, providing the first explanation for the presence of the intermediate Newtonian plateau along with reproducing the second shear thinning in a single framework. Expressions utilized for various interactions and friction are determined from experimental measurements and hence, result in an excellent quantitative agreement between the simulations and previous experiments.

42 ENGINEERING↗

A simple catch: Fluctuations enable hydrodynamic trapping of microrollers by obstacles

It is known that obstacles can hydrodynamically trap bacteria and synthetic microswimmers in orbits, where the trapping time heavily depends on the swimmer flow field and noise is needed to escape the trap. Here, we use experiments and simulations to investigate the trapping of microrollers by obstacles. Microrollers are rotating particles close to a bottom surface, which have a prescribed propulsion direction imposed by an external rotating magnetic field. The flow field that drives their motion is quite different from previously studied swimmers. We found that the trapping time can be controlled by modifying the obstacle size or the colloid-obstacle repulsive potential. We detail the mechanisms of the trapping and find two remarkable features: The microroller is confined in the wake of the obstacle, and it can only enter the trap with Brownian motion. While noise is usually needed to escape traps in dynamical systems, here, we show that it is the only means to reach the hydrodynamic attractor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Entropy production fluctuations encode collective behavior in active matter

We derive a general lower bound on distributions of entropy production in interacting active matter systems. The bound is tight in the limit that interparticle correlations are small and short-ranged, which we explore in four canonical active matter models. In all models studied, the bound is weak where collective fluctuations result in long-ranged correlations, which subsequently links the locations of phase transitions to enhanced entropy production fluctuations. We develop a theory for the onset of enhanced fluctuations and relate it to specific phase transitions in active Brownian particles. Furthermore, we also derive optimal control forces that realize the dynamics necessary to tune dissipation and manipulate the system between phases. In so doing, we uncover a general relationship between entropy production and pattern formation in active matter, as well as ways of controlling it.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Probing the Self-Assembly dynamics of cellulose nanocrystals by X-ray photon correlation spectroscopy

Charge-stabilized colloidal cellulose nanocrystals (CNCs) can self-assemble into higher-ordered chiral nematic structures by varying the volume fraction. The assembly process exhibits distinct dynamics during the isotropic to liquid crystal phase transition, which can be elucidated using X-ray photon correlation spectroscopy (XPCS). Anionic CNCs were dispersed in propylene glycol (PG) and water spanning a range of volume fractions, encompassing several phase transitions. Coupled with traditional characterization techniques, XPCS was conducted to monitor the dynamic evolution of the different phases. Additionally, simulated XPCS results were obtained using colloidal rods and compared with the experimental data, offering additional insights into the dynamic behavior of the system. The results indicate that the particle dynamics of CNCs undergo a stepped decay in three stages during the self-assembly process in PG, coinciding with the observed phases. The phase transitions are associated with a total drop of Brownian diffusion rates by four orders of magnitude, a decrease of more than a thousand times slower than expected in an ideal system of repulsive Brownian rods. Given the similarity in the phase behaviors in CNCs dispersed in PG and in water, we hypothesize that these dynamic behaviors can be extrapolated to other polar solvent environments. Importantly, these findings represent the direct measurement of CNC dynamics using XPCS, underscoring the feasibility of directly assessing the dynamic behavior of other rod-like colloidal suspensions.

36 MATERIALS SCIENCE↗

Label-Free Anti-Brownian Trapping of Single Nanoparticles in Solution

Today, biomolecular nanoparticles are prevalent as diagnostic tools and molecular delivery carriers, and it is particularly useful to examine individuals within a sample population to quantify the variations between objects and directly observe the molecular dynamics involving these objects. Using interferometric scattering as a highly sensitive label-free detection scheme, we recently developed the interferometric scattering anti-Brownian electrokinetic (ISABEL) trap to hold a single nanoparticle in solution for extended optical observation. In this perspective, we describe how we implemented this trap, how it extends the capabilities of previous ABEL traps, and how we have begun to study individual carboxysomes, a fascinating biological carbon fixation nanocompartment. By monitoring single nanocompartments for seconds to minutes in the ISABEL trap using simultaneous interferometric scattering and fluorescence spectroscopy, we have demonstrated single-compartment mass measurements, cargo-loading trends, and redox sensing inside individual particles. These experiments benefit from rich multiplexed correlative measurements utilizing both scattering and fluorescence with many exciting future capabilities within reach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Topology induced crossover between Langevin, subdiffusion, and Brownian diffusion regimes in supercooled water

Despite extensive studies of supercooled water, it remains challenging to understand its peculiar dynamic anomalous properties. In this work, we integrated full atomistic simulations of supercooled water over the temperature range of room temperature to 200 K using a quantum-mechanics-based polarizable force field with the dressed dynamics method that couples fast collision events and slow reorganization dynamics of hydrogen-bond networks. Our analysis unveils the salient multiscale features in the transient relaxation dynamics of supercooled water. A classical Langevin behavior dominates at fast timescales, while long-time relaxations unveil two different activation barriers in two temperature regions: below and above 230 K. The modulation of the entropy spectrum by temperature is elucidated in terms of a three-state model underlined by the complexity of the water dynamics associated with a topological transition of a strong hydrogen-bond network. This state-dependent network topology is quantitatively characterized by power-law exponents of inverse network connectivity from 200 to 298 K. Finally, this work provides valuable guidance for further studies on the transient relaxation dynamics of supercooled water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High resolution atomic force microscopy with an active piezoelectric microcantilever

Active microcantilevers with on-chip sensing and actuation provide significant advantages in tapping mode Atomic Force Microscopy (AFM). Collocated transduction allows for effective manipulation of cantilever dynamics through feedback control, enabling higher scan rates. However, the adjacency of the sensing and actuation electrodes is known to result in a high level of feedthrough, leading to a low imaging resolution. Readout circuit noise further deteriorates the imaging precision. Here, we investigate the noise sources that affect AFM microcantilevers with collocated aluminum nitride (AlN) actuator–sensor pairs. We reported these cantilevers in earlier work and demonstrated that they display a very low level of feedthrough between the actuation and sensing electrodes. We present a high signal-to-noise ratio (SNR) sensing method that enables us to demonstrate high-resolution AFM on a calibration grating with nm-step silicon carbide (SiC) terraces. In conclusion, measuring the Lorentzian response of the cantilever’s Brownian motion with the on-chip active sensor at resonance enables us to calibrate the dynamic stiffness at the first fundamental resonance mode, without utilizing an optical sensor.

47 OTHER INSTRUMENTATION↗

Primary fission fragment mass yields across the chart of nuclides

In this work, we have calculated a complete set of primary fission fragment mass yields, Y(A), for heavy nuclei across the chart of nuclides, including those of particular relevance to the rapid neutron capture process (r process) of nucleosynthesis. We assume that the nuclear shape dynamics are strongly damped, which allows for a description of the fission process via Brownian shape motion across nuclear potential-energy surfaces. The macroscopic energy of the potential was obtained with the Finite-Range Liquid-Drop Model (FRLDM), while the microscopic terms were extracted from the single-particle level spectra in the fissioning system by the Strutinsky procedure for the shell energies and the BCS treatment for the pairing energies. For each nucleus considered, the fission fragment mass yield, Y(A), is obtained from 50 000 to 500 000 random walks on the appropriate potential-energy surface. The full mass and charge yield, Y(Z,A), is then calculated by invoking the Wahl systematics. With this method, we have calculated a comprehensive set of fission-fragment yields from over 3800 nuclides bounded by 80 ≤ Z ≤ 130 and A ≤ 330; these yields are provided as an ASCII formatted database in the Supplemental Material. We compare our yields to known data and discuss general trends that emerge in low-energy fission yields across the chart of nuclides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗