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At least 1,189 records · Page 66

Probing gluon saturation with forward di-hadron correlations in proton-nucleus collisions

We present a detailed numerical investigation of semi-inclusive forward di-hadron production in proton–nucleus collisions employing the Color Glass Condensate effective theory. We focus on the regime where di-hadrons are produced nearly back-to-back in the transverse plane, thereby justifying a transverse-momentum-dependent factorization approach in terms of small-x gluon distributions. Our computation integrates several key elements: i) non-linear rapidity evolution via the Balitsky–Kovchegov equation with running coupling, ii) both perturbative and non-perturbative Sudakov resummation, and iii) a phenomenologically constrained model for the initial conditions for small-x gluon distributions. We compare this phenomenological framework to experimental data from the STAR Collaboration on azimuthal correlations in forward di-pion production in both proton–proton and proton–gold collisions. We analyze the systematic theoretical uncertainties associated with the saturation scales of nuclei at the initial scale for rapidity evolution and with those associated with the hadronization process. Finally, we make predictions for the kinematics anticipated to be covered by the ALICE Forward Calorimeter (FoCal) upgrade at the Large Hadron Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Non-equilibrium phenomena and kinetic pathways in self-assembled polyelectrolyte complexes

Polyelectrolyte complexation has been conventionally focused on the thermodynamic states, where assemblies have equilibrated in solutions. Far less attention has been given to complex systems that are kinetically trapped at non-equilibrium states. A combination of time-resolved dynamic light scattering, small angle X-ray scattering (SAXS), and cryogenic transmission electron microscopy (Cryo-TEM) was employed here to investigate the internal structures and morphological evolution of non-equilibrium aggregates forming from a pair of two strong block polyelectrolytes over wide time and length scales. The role of formation pathways of electrostatically driven aggregates was assessed using two processing protocols: direct dissolution and salt annealing. The former led to thermodynamically stable products, while the latter resulted in kinetically trapped transient structures. After adding salt, the metastable structures gradually transformed into stable products. Cryo-TEM images showed the interconnected irregular morphologies of the aggregates, and SAXS data revealed the presence of fuzzy globular complexes with R-g similar to 10 nm within them. A two-step process in the time-dependent structural transformation was found and characterized by a fast breakdown of interconnected transient aggregates followed by a slow redistribution of the incipient individual electrostatic assemblies. Furthermore, the prolonged aggregate disintegration process fitting to a stretched exponential function unveiled the broad relaxation distribution and significant structural heterogeneity in these polyelectrolyte complex nanoaggregates. This work brings new insight into the comprehension of non-equilibrium phenomena in self-assembled electrostatic assemblies and represents a first step toward constructing far-from-equilibrium polyelectrolyte complexes de novo for future applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Leveraging Pre-Built Catalogs and Object-Level Scheduling to Eliminate I/O Bottlenecks in HPC Environments

Modern High-Performance Computing (HPC) environments face mounting challenges due to the shift from large to small file datasets, along with an increasing number of users and parallelized applications. As HPC systems rely on Parallel File Systems (PFS), such as Lustre for data processing, performance bottlenecks stemming from Object Storage Target (OST) contention have become a significant concern. Existing solutions, such as LADS with its object-level scheduling approach, fall short in large-scale HPC environments due to their inability to effectively address metadata I/O bottlenecks and the growing number of I/O processes. This study highlights the pressing need for a comprehensive solution that tackles both OST contention and metadata I/O challenges in diverse HPC workloads. To address these challenges, we propose SwiftLoad, an object-level I/O scheduling framework that leverages a metadata catalog to enhance the performance and efficiency of parallel HPC utilities. The adoption of the metadata catalog mitigates the metadata I/O bottlenecks that commonly occur in HPC utilities, a challenge that is particularly pronounced in object-level I/O scheduling. SwiftLoad addresses OST contention and the uneven distribution of I/O processes across different OSTs through mathematical modeling and incorporates a Loader Configuration Module to regulate the number of I/O processes. Evaluated with two representative utilities—data deduplication profiling and data augmentation—SwiftLoad achieved performance improvements of up to 5.63x and 11.0x, respectively, on a production supercomputer.

HPC↗

Pretraining Billion-Scale Geospatial Foundational Models on Frontier

As AI workloads increase in scope, generalization capability becomes challenging for small task-specific models and their demand for large amounts of labeled training samples increases. On the contrary, Foundation Models (FMs) are trained with internet-scale unlabeled data via self-supervised learning and have been shown to adapt to various tasks with minimal fine-tuning. Although large FMs have demonstrated significant impact in natural language processing and computer vision, efforts toward FMs for geospatial applications have been restricted to smaller size models, as pretraining larger models requires very large computing resources equipped with state-of-the-art hardware accelerators. Current satellite constellations collect 100+TBs of data a day, resulting in images that are billions of pixels and multimodal in nature. Such geospatial data poses unique challenges opening up new opportunities to develop FMs. We investigate billion scale FMs and HPC training profiles for geospatial applications by pretraining on publicly available data. We studied from end-to-end the performance and impact in the solution by scaling the model size. Our larger 3B parameter size model achieves up to 30% improvement in top1 scene classification accuracy when comparing a 100M parameter model. Moreover, we detail performance experiments on the Frontier supercomputer, America's first exascale system, where we study different model and data parallel approaches using PyTorch's Fully Sharded Data Parallel library. Specifically, we study variants of the Vision Transformer architecture (ViT), conducting performance analysis for ViT models with size up to 15B parameters. By discussing throughput and performance bottlenecks under different parallelism configurations, we offer insights on how to leverage such leadership-class HPC resources when developing large models for geospatial imagery applications.

Tsaris, Aristeidis (aris)↗

SubKit

Generating a CTF (thermal-hydraulics subchannel code) model can be time consuming and error prone because of the rigid formatting of the input file and the amount of input requirements. Because of the structured input format, making small changes to a model can require large scale changes to the input file. Furthermore, a user typically has to perform calculations to develop CTF input parameters from actual model geometry. Changing model geometry requires re-calculating input parameters and copying them from wherever the calculation was performed, be it a script, spreadsheet, or piece of paper. This process complicates the quality assurance process for that model and makes changing the model more difficult. CtfDeckBuilder is an object-oriented Python interface to CTF that allows the user to build a CTF model in Python. The user no longer needs to interface with the CTF input file when using the CtfDeckBuilder. The interface reduces the information required of the user by offering defaults for most modeling options provided by CTF. The user can perform calculations directly in Python when building the model so that calculations stay with the model itself.

Salko, Jr., RobertK↗

Discrete Fracture Network Modeling to Estimate Upscaled Parameters for the Topopah Spring, Lava Flow, and Tiva Canyon Aquifers at Pahute Mesa, Nevada National Security Site

This report describes the results of Discrete Fracture Network (DFN) simulations for the Topopah Spring Aquifer (TSA), Lava Flow Aquifer, and Tiva Canyon Aquifer (TCA), at Pahute Mesa on the Nevada National Security Site (NNSS), formerly the Nevada Test Site. The research focuses on calculating upscaled groundwater flow and contaminant transport parameters using DFNs generated according to fracture characteristics observed in the TSA, LFA and TCA at Pahute Mesa. The highly fractured and heterogeneous nature of these aquifers makes them candidates for stochastic DFN modeling of radionuclide transport on a small scale with subsequent upscaling. One hundred independent DFN realizations are generated for each aquifer, and the upscaled parameters for continuum simulations of subsurface flow and transport in fractured media at Pahute Mesa are calculated. Our goal is to implement a modeling approach that can translate parameters to larger-scale models that account for local-scale flow and transport processes, such as channelization of flow and transport along a few well connected, large fractures. Additionally, to simulate advective and advective-diffusive transport through the fracture networks, the Time Domain Random Walk (TDRW) approach is applied to account for matrix diffusion into a finite half-space. Moreover, a novel approach to calculate dynamic (active) fracture surface area to reflect flow channeling is implemented. This work will improve the representation of radionuclide transport processes in largescale, regulatory-focused models by providing estimates of hard-to-measure flow and contaminant transport parameters at large scales. In this report, we (1) show recent results of flow and transport simulations on multiple DFN realizations of the TSA, LFA, TCA; (2) discuss the resulting distributions of estimated upscaled parameters; (3) describe the estimation of upscaled parameters for an equivalent parallel-plate continuum model and (4) present a comparison between simulated transport from the equivalent continuum model and an actual DFN.

54 ENVIRONMENTAL SCIENCES↗

Development and Advanced Testing of DPC Cement Fillers

The fillers research and development (R&D) program, mostly experimental, is part of a broader R&D program that includes new process modeling and performance assessment of criticality effects and the overall importance of criticality to repository performance (consequence screening). A literature research and consultation effort with experts by Hardin and Brady (2018) identified several potentially effective and workable filler materials including cements (primarily phosphate based), moltenmetal alloys, and low-temperature glasses. Filler attributes were defined, and the preliminary lists were compared qualitatively. Further comparative analysis will be done (e.g., cost estimates) after experimental screening has narrowed the list of alternatives. The research presented here is focused Sandia’s efforts for the development of phosphate-based cement fillers. Molten metal filler research is an ongoing activity at Oak Ridge National Laboratories and is not discussed herein. After the completion of the FY20 research effort the following cement filler compositions were selected for further experimental development work and advanced testing in FY21: 1. Aluminum phosphate cements (APCs); more specifically aluminum oxide / aluminum phosphate (Al 2 O 3 / AlPO 4 ) cements in which Al 2 O 3 serves as the filler material bound by an AlPO 4 binder formed by the reaction of Al 2 O 3 with various phosphate sources; 2. Wollastonite phosphate cements (WPCs), specifically wollastonite and aluminum or calcium aluminum phosphates in which CaSiO 3 serves as the filler material bound by a calcium phosphate that serves as the binder; and 3. Calcium aluminate phosphate cements (CAPCs) specifically grossite (CaAl 4 O 7 ) and hibonite (CaAl 11 O 18 ) fillers bound by an aluminum phosphate that serves as the binder. This effort focused on the optimization and subsequent processing of these three cements to achieve dense and well-consolidated monolithic samples. Upon completion of the FY21 effort the aluminum phosphate cements (APCs) and the calcium aluminate phosphate cements (CAPCs) show the most promise for advanced testing and scale up. We will begin the work in FY22 focused on testing the performance of these two cements in small scale DPCs as well as advanced materials testing to evaluate cement performance under expected radiation doses and representative post-closure geochemical environments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Heat shield characterization: Outer planet atmospheric entry probe

A full scale carbon phenolic heat shield was fabricated for the Outer Planet Probe in order to demonstrate the feasibility of molding large carbon phenolic parts with a new fabrication processing method (multistep). The sphere-cone heat shield was molded as an integral unit with the nose cap plies configured into a double inverse chevron shape to achieve the desired ply orientation. The fabrication activity was successful and the feasibility of the multistep processing technology was established. Delaminations or unbonded plies were visible on the heat shield and resulted from excessive loss of resin and lack of sufficient pressure applied on the part during the curing cycle. A comprehensive heat shield characterization test program was conducted, including: nondestructive tests with the full scale heat shield and thermal and mechanical property tests with small test specimen.

Mezines, S. A.↗

Effect of fuel injector type on performance and emissions of reverse-flow combustor

The combustion process in a reverse-flow combustor suitable for a small gas turbine engine was investigated to evaluate the effect of fuel injector type on performance and emissions. Fuel injector configurations using pressure-atomizing, spill-flow, air blast, and air-assist techniques were compared and evaluated on the basis of performance obtained in a full-scale experimental combustor operated at inlet conditions corresponding to takeoff, cruise, low power, and idle and typical of a 16:1-pressure-ratio turbine engine. Major differences in combustor performance and emissions characteristics were experienced with each injector type even though the aerodynamic configuration was common to most combustor models. Performance characteristics obtained with the various fuel injector types could not have been predicted from bench-test injector spray characteristics. The effect of the number of operating fuel injectors on performance and emissions is also presented.

Norgren, C. T.↗

Numerical Simulation of the Instability of an Inviscid Liquid Jet in a Coflowing Compressible Airstream

The nonlinear interfacial instability of a liquid jet in a coflowing compressible airstream is studied numerically. A high-resolution scheme which has second-order accuracy in space and time is coupled with a Lagrangian marker particle algorithm to visualize the large-scale motion of the interfaces in compressible flow. A numerical algorithm based on an approximate equation of state of a compressible liquid is developed to allow this two-fluid system to be governed by the nonlinear unsteady Euler equations in conservative form. The initial growth of small disturbances given by the simulations agrees well with linear theory. The process of jet disruption in compressible flow is demonstrated to consist of the formation of liquid spikes, interweaving of the gas and liquid and stretching and detachment of the liquid main center core.

Li, H. -S.↗

A Lightweight I/O Scheme to Facilitate Spatial and Temporal Queries of Scientific Data Analytics

In the era of petascale computing, more scientific applications are being deployed on leadership scale computing platforms to enhance the scientific productivity. Many I/O techniques have been designed to address the growing I/O bottleneck on large-scale systems by handling massive scientific data in a holistic manner. While such techniques have been leveraged in a wide range of applications, they have not been shown as adequate for many mission critical applications, particularly in data post-processing stage. One of the examples is that some scientific applications generate datasets composed of a vast amount of small data elements that are organized along many spatial and temporal dimensions but require sophisticated data analytics on one or more dimensions. Including such dimensional knowledge into data organization can be beneficial to the efficiency of data post-processing, which is often missing from exiting I/O techniques. In this study, we propose a novel I/O scheme named STAR (Spatial and Temporal AggRegation) to enable high performance data queries for scientific analytics. STAR is able to dive into the massive data, identify the spatial and temporal relationships among data variables, and accordingly organize them into an optimized multi-dimensional data structure before storing to the storage. This technique not only facilitates the common access patterns of data analytics, but also further reduces the application turnaround time. In particular, STAR is able to enable efficient data queries along the time dimension, a practice common in scientific analytics but not yet supported by existing I/O techniques. In our case study with a critical climate modeling application GEOS-5, the experimental results on Jaguar supercomputer demonstrate an improvement up to 73 times for the read performance compared to the original I/O method.

Temporal Queries↗

Development of Biomorphic Flyers

Biomorphic flyers have recently been demonstrated that utilize the approach described earlier in "Bio-Inspired Engineering of Exploration Systems" (NPO-21142), NASA Tech Briefs, Vol. 27, No. 5 (May 2003), page 54, to distill the principles found in successful, nature-tested mechanisms of flight control. Two types of flyers are being built, corresponding to the imaging and shepherding flyers for a biomorphic mission described earlier in "Cooperative Lander- Surface/Aerial Microflyer Missions for Mars Exploration" (NPO-30286), NASA Tech Briefs, Vol. 28, No. 5 (May 2004), page 36. The common features of these two types of flyers are that both are delta-wing airplanes incorporating bio-inspired capabilities of control, navigation, and visual search for exploration. The delta-wing design is robust to approx.40 G axial load and offers ease of stowing and packaging. The prototype that we have built recently is shown in the figure. Such levels of miniaturization and autonomous navigation are essential to enable biomorphic microflyers (<1 kg) that can be deployed in large numbers for distributed measurements and exploration of difficult terrain while avoiding hazards. Individual bio-inspired sensors that will be incorporated in a biomorphic flyer have been demonstrated recently. These sensors include a robust, lightweight (~6 g), and low-power (~40 mW) horizon sensor for flight stabilization. It integrates successfully the principles of the dragonfly ocelli. The ocelli are small eyes on the dorsal and forward regions of the heads of many insects. The ocelli are distinct from the compound eyes that are most commonly associated with insect vision. In many insects, the ocelli are little more than single-point detectors of short-wavelength light and behavioral responses to ocelli stimuli are hard to observe. The notable exception is found in dragonflies, where flight control is notably degraded by any interference with the ocellar system. Our team has discovered recently that the ocelli are a dedicated horizon sensor, with substantial optical processing and multiple spectral sensitivity. To our knowledge, this is the world s first demonstrated use of a "biomorphic ocellus" as a flight-stabilization system. The advantage of the ocelli over a similarly sized system of rate gyroscopes is that both attitude control and rate damping can be realized in one device. A full inertial unit and significant processing would otherwise be required to achieve the same effect. As a prelude to full autonomy, substantial stability augmentation is provided to the pilot at very low cost in terms of space, power, and mass. The sensor is about 40 times lighter than a comparable inertial attitude reference system. Other significant features of the biomorphic flyer shown in the figure include its ability to fly at high angles of attack ~30 and a deep wing chord which allows scaling to small size and low Reynold s number situations. Furthermore, the placement of the propulsion system near the center of gravity allows continued control authority at low speeds. These attributes make such biomorphic flyers uniquely suited to planetary and terrestrial exploration where small size and autonomous airborne operation are required.

Thakoor, Sarita↗

From Fluid Flow to Coupled Processes in Fractured Rock: Recent Advances and New Frontiers

Abstract Quantitative predictions of natural and induced phenomena in fractured rock is one of the great challenges in the Earth and Energy Sciences with far‐reaching economic and environmental impacts. Fractures occupy a very small volume of a subsurface formation but often dominate fluid flow, solute transport and mechanical deformation behavior. They play a central role in CO 2 sequestration, nuclear waste disposal, hydrogen storage, geothermal energy production, nuclear nonproliferation, and hydrocarbon extraction. These applications require predictions of fracture‐dependent quantities of interest such as CO 2 leakage rate, hydrocarbon production, radionuclide plume migration, and seismicity; to be useful, these predictions must account for uncertainty inherent in subsurface systems. Here, we review recent advances in fractured rock research covering field‐ and laboratory‐scale experimentation, numerical simulations, and uncertainty quantification. We discuss how these have greatly improved the fundamental understanding of fractures and one's ability to predict flow and transport in fractured systems. Dedicated field sites provide quantitative measurements of fracture flow that can be used to identify dominant coupled processes and to validate models. Laboratory‐scale experiments fill critical knowledge gaps by providing direct observations and measurements of fracture geometry and flow under controlled conditions that cannot be obtained in the field. Physics‐based simulation of flow and transport provide a bridge in understanding between controlled simple laboratory experiments and the massively complex field‐scale fracture systems. Finally, we review the use of machine learning‐based emulators to rapidly investigate different fracture property scenarios and accelerate physics‐based models by orders of magnitude to enable uncertainty quantification and near real‐time analysis.

58 GEOSCIENCES↗

Simulation of high-frequency dissolved oxygen dynamics in a shallow estuary, the Corsica River, Chesapeake Bay

Understanding shallow water biogeochemical dynamics is a challenge in coastal regions, due to the presence of highly variable land-water interface fluxes, tight coupling with sediment processes, tidal dynamics, and diurnal variability in biogeochemical processes. While the deployment of continuous monitoring devices has improved our understanding of high-frequency (12 - 24 hours) variability and spatial heterogeneity in shallow regions, mechanistic modeling of these dynamics has lagged behind conceptual and empirical models. The inherent complexity of shallow water systems is represented in the Corsica River estuary, a small basin within the Chesapeake Bay ecosystem, where abundant monitoring data have been collected from long-term monitoring stations, continuous monitoring sensors, synoptic sensor surveys, and measurements of sediment-water fluxes. A state-of-the-art modeling system, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), was applied to the Corsica domain with a high-resolution grid and nutrient loads from the most recent version of the Chesapeake Bay watershed model. The Corsica SCHISM model reproduced observed high-frequency variability in dissolved oxygen, as well as seasonal variability in chlorophyll-a and sediment-water fluxes. Time-series signal analyses using Empirical Model Decomposition and spectral analysis revealed that the diurnal and M2 tide frequencies are the dominant high-frequency modes and physical transport contributes a larger share to dissolved oxygen budgets than biogeochemical processes on an hourly time scale. Heterogeneity and patchiness in dissolved oxygen resulting from phytoplankton distributions and geometry-driven eddies amplify the physical transport effect, and on longer time scales oxygen is controlled more by photosynthesis and respiration. Our simulation demonstrates that interactions among physical and biological dynamics generate complex high-frequency variability in water quality and non-linear reposes to nutrient loading and environmental forcing in shallow water systems.

54 ENVIRONMENTAL SCIENCES↗

Long‐Range Electron Transport Rates Depend on Wire Dimensions in Cytochrome Nanowires

Abstract The ability to redirect electron transport to new reactions in living systems opens possibilities to store energy, generate new products, or probe physiological processes. Recent work by Huang et al. showed that 3D crystals of small tetraheme cytochromes (STC) can transport electrons over nanoscopic to mesoscopic distances by an electron hopping mechanism, making them promising materials for nanowires. However, fluctuations at room temperature may distort the nanostructure, hindering efficient electron transport. Classical molecular dynamics simulations of these fluctuations at the nano‐ and mesoscopic scales allowed us to develop a graph network representation to estimate maximum electron flow that can be driven through STC wires. In longer nanowires, transient structural fluctuations at protein‐protein interfaces tended to obstruct efficient electron transfer, but these blockages are ameliorated in thicker crystals where alternative electron transfer pathways become more efficient. The model implies that more flexible proteinprotein interfaces limit the required minimum diameter to carry currents commensurate with conventional electronics.

Chemistry↗

Future Trends in Nuclear Physics Computing

In nuclear physics (NP) today the study of quarks, gluons and their strong interactions extends across a broad research program at a varied range of collaborative scales, from a few collaborators up to large experiments at scales comparable to those typical of high energy physics (HEP). Overall, the software and computing efforts vary accordingly, from pragmatic do-it-yourself approaches among a few, to substantial organized software and computing activities within large experiments. With new experiments starting up and on the horizon [1], and rapidly increasing data volumes [2, 3] and processing demands even at small experiments, the NP community has in recent years been thinking about the next generation of data processing and analysis workflows that will maximize the science output. One context for this discussion has been a series of workshops, “Future Trends in Nuclear Physics Computing” [4]. The most recent in this series took place in Fall 2020, organized by the authors together with colleagues. The workshop focused on identifying the unique aspects of software and computing in NP, and discussing how the NP community could strengthen common efforts and chart a path forward for the next decade, sure to be an exciting one with rich ongoing scientific programs at Brookhaven National Laboratory (BNL), Jefferson Lab (JLab), and other NP facilities, and culminating in datataking at the Electron-Ion Collider (EIC) [5,6,7] in the early 2030s. Without claiming to present a collective view from the workshop and discussions since—fortunately this is not expected of us in this opinion editorial—we offer here our reflections on the topic, informed by the workshop and the summary we authored with our colleagues [8], as well as discussions and developments in the eventful time since.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Defects Enable Dark Exciton Photoluminescence in Single-Walled Carbon Nanotubes

Variable temperature photoluminescence excitation spectroscopy of three (n,m) species of single-walled carbon nanotubes revealed that at resonant S 22 excitation, in addition to allowed excitonic optical transitions, several sidebands that should be forbidden based on selection rules were observed and appeared to have a strong temperature dependence. In particular, we found that a sideband located approximately 130 meV away from the bright S 11 exciton peak relating to the K-momentum dark exciton state, called X 1 , decreased in intensity five-fold as the samples were cooled. Direct optical excitation of this dark state is nominally forbidden, thus calling into question how the state is populated, and why it is so prominent in the photoluminescence spectrum. Interestingly, the ratio of the integrated photoluminescence intensities of X 1 to S 11 scales with a Boltzmann factor unrelated to the phonon that is thought to be responsible for depopulating the K-momentum dark exciton state: an in-plane transverse optical phonon, A 1 ’. Furthermore, photoluminescence spectra from individual (7,5) nanotubes show that only a small fraction exhibit the X 1 feature, with varying oscillator strength, thus suggesting that intrinsic processes such as phonon scattering are not responsible for populating the dark state. Alternatively, we suggest that populating the K-momentum dark exciton state requires scattering from defects, which is consistent with the increased magnitude of the X 1 feature for samples with increased sample purification and processing. Thus, the presence of an X 1 peak in photoluminescence is an extremely sensitive spectroscopic indicator of defects on single-walled carbon nanotubes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Smoother Surfaces Enhance Diffusion of Nanorods in Entangled Polymer Melts

Coarse-grained molecular dynamics simulations are used to study the diffusion of thin nanorods in entangled polymer melts for varying nanorod length and roughness. While prior studies observed a nanorod parallel diffusion constant scaling inversely with rod length D ∥ ~ l –1 , here, we show that this scaling is not universal and depends sensitively on the nanorod surface roughness. We observe D ∥ ~ l –k , where k < 1 and decreases with decreasing surface roughness. The weaker scaling is driven by the non-Gaussian diffusion of nanorods due to the emergence of an intermittent hopping process that becomes more pronounced with decreasing roughness at the monomer scale. Analysis shows that the mean hop size grows for smoother rods but shows little to no variation with rod length. The mean hopping frequency shows no dependence on either rod length or roughness, suggesting it originates from the polymer melt environment. Further, our results show that the small-scale features of the nanorod surface strongly influence the large-scale and long-time transport of nanorods in polymer matrices, creating new material design opportunities for precisely engineered nanocomposites.

77 NANOSCIENCE AND NANOTECHNOLOGY↗