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At least 127 records · Page 7

Faster network disruption from layered oscillatory dynamics

Nonlinear complex network-coupled systems typically have multiple stable equilibrium states. Following perturbations or due to ambient noise, the system is pushed away from its initial equilibrium, and, depending on the direction and the amplitude of the excursion, it might undergo a transition to another equilibrium. It was recently demonstrated [M. Tyloo, J. Phys. Complex. 3 03LT01 (2022)] that layered complex networks may exhibit amplified fluctuations. Here, I investigate how noise with system-specific correlations impacts the first escape time of nonlinearly coupled oscillators. Interestingly, I show that, not only the strong amplification of the fluctuations is a threat to the good functioning of the network but also the spatial and temporal correlations of the noise along the lowest-lying eigenmodes of the Laplacian matrix. Finally, I analyze first escape times on synthetic networks and compare noise originating from layered dynamics to uncorrelated noise.

97 MATHEMATICS AND COMPUTING↗

Probing iron in Earth’s core with molecular-spin dynamics

Dynamic compression of iron to Earth-core conditions is one of the few ways to gather important elastic and transport properties needed to uncover key mechanisms surrounding the geodynamo effect. Herein, a machine-learned ab initio derived molecular-spin dynamics (MSD) methodology with explicit treatment for longitudinal spin-fluctuations is utilized to probe the dynamic phase-diagram of iron. This framework uniquely enables an accurate resolution of the phase-transition kinetics and Earth-core elastic properties, as highlighted by compressional wave velocity and adiabatic bulk moduli measurements. In addition, a unique coupling of MSD with time-dependent density functional theory enables gauging electronic transport properties, critically important for resolving geodynamo dynamics.

58 GEOSCIENCES↗

Ab initio calculations for void swelling bias in α - and δ -plutonium

Void swelling can develop in materials under persistent irradiation when nonequilibrium vacancy and self-interstitial populations migrate under sufficiently asymmetric interaction biases. In conventional metals, the propensity is determined to the first approximation by comparing point-defect relaxation strains. We thus present DFT-based calculations of structures and formation energies and volumes of point defects in the α and the δ phases of plutonium. Here we discuss the pros and cons of various levels of electronic structure theory: spin polarization, spin-orbit coupling, and orbital polarization. Our results show that lattice defects in δ-Pu, in contrast to most fcc metals, have surprisingly small formation volumes. Equally unexpected are the large defect formation volumes found in the low-symmetry α-Pu phase. Both these unusual properties can be satisfactorily explained from defect-induced spin/orbital moment formation and destruction in the Pu phases. Surprisingly, the point defects in α-Pu are found to induce far larger transformation of the local electronic structure than in δ-Pu. When we use the calculated defect properties to estimate the classic void swelling bias in each of the phases, we find it to be unusually small in δ-Pu but likely much larger in α-Pu. Hence, swelling rates and mechanisms can diverge dramatically between the different phases of Pu. Especially in the transient regime before the formation of large defect clusters, the swelling rate of α-Pu can reliably be expected to be much larger than δ-Pu. However, accurate forecasts over longer times will require the conventional void-swelling theory to be modified to handle the complexities presented by the different Pu phases. As a case in point, we show the possible anomalous temperature dependence of vacancy properties in δ-Pu, caused by entropic contributions from defect-induced spin-lattice fluctuations. Such complications may affect defect-defect interactions and thus alter the void swelling bias.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

FEED Study of Carbon Capture Inc. DAC and CarbonCure Utilization Using United States Steel's Gary Works Waste Plant

Direct Air Capture (DAC) has been proposed as a means of reducing atmospheric concentrations of CO2. While DAC has been evaluated through lab-scale, bench-scale, and small-scale pilot units, large-scale deployment has not been achieved. Feasibility studies are one tool to understand the potential design, operation, performance, and impact of commercial-scale DAC. This paper presents the results of a feasibility study for a passive DAC system deployed at >100,000 tpy scale in three different regions across the U.S. and awarded to Carbon Collect by the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL). The MechanicalTree™technology has been designed and engineered by Carbon Collect based on the concept initially developed at Arizona State University Center for Negative Carbon Emissions. It uses a tower of stacked, sorbentcontaining disks supported by a lifting mechanism, exposed to the air to capture CO2 during the adsorption phase. The disks are then lowered into a regeneration chamber for vacuum and steam regeneration to produce CO2 product during the desorption step. The modular tree design allows large installations with repeatable, mass-manufactured units connected to common utilities such as steam supply, vacuum, and CO2 processing for compression and geologic storage. The passive DAC system eliminates the equipment and energy of forced air fans by using natural air circulation to contact the sorbent with the CO2 in the air. Because of this, the performance is dependent on the wind speed in addition to the temperature and relative humidity. Performance and flow rate fluctuations were incorporated into equipment and facility design with considerations for turndown to 10% of maximum rated flow to allow operation in all seasons. The feasibility study was undertaken to evaluate the technology in different regions and climates. Three locations were selected for this study representing different climates: Alabama (hot and humid), California (hot and arid), and Wyoming (continental). For each region, the adsorption/desorption cycle was optimized including tuning the heat integration and cycle timings. The performance of individual trees was then scaled to the full facility with the same design of more than 20,000 trees common between all regions. The installations had expected average CO2 capture rates of between 330,000 and 485,000 tonnes of CO2 per year depending on the climate. The initial engineering design for the facility at each location was performed with cost and performance estimates for the trees, carbon purification and compression, and the balance of plant. To supply thermal and electrical energy for the facility, carbon-free or low-carbon power must be considered. Options for low-carbon, continuous thermal and electrical energy were considered. The best-performing option from those considered was identified to be an electrically-heated molten salt energy storage system, powered by an on-site photovoltaic field. During molten salt thermal discharge, steam is produced from heat exchange with the molten salt and used to generate power in a steam turbine as well as steam for regenerating the DAC carbon trees. The thermal and electrical supply and analysis is presented in the context of low-carbon power for carbon removal. Modelling and economics of transportation and geologic storage of the CO2 is considered and presented for each location. The results of the feasibility study are incorporated into the presented techno-economic and life-cycle assessments. This work is intended to provide an understanding of the performance, cost, and impact of capturing CO2 at the commercial scale and the impact of climate and regional siting on the considered passive DAC system.

42 ENGINEERING↗

Statistical analysis of magnetic divertor configuration influence on H-mode transitions

DIII-D plasmas are compared for two upper divertor configurations: with the outer strike point on the small angle slot (SAS) divertor target and with the outer strike point on the horizontal divertor target (HT). Scanning the vertical distance between the magnetic null point and the divertor target over a range 0.10–0.16 m is shown to increase the threshold power, $P_\mathrm{th}$, and edge plasma power, $P_\mathrm{Loss},$ for the low-to-high confinement (L–H) and H–L transitions respectively, by up to a factor of 1.4. The X-point height scans were performed at three L-mode core plasma line average electron densities, $\bar{n}_\mathrm{e} = $ 1.2, 2.2 and 3.6 $\times 10^{19}\,\mathrm{m}^{-3}$, to investigate the density dependence of divertor magnetic configuration influence on $P_\mathrm{th}$. The X-point height, $Z_\textrm{x-pt}$, was further extended across the range 0.16–0.22 m with the more open HT divertor configuration, for which a clear decrease in $P_\mathrm{th}$ with increasing $Z_\textrm{x-pt}$ is observed. The dependence of $P_\textrm{th}$ on divertor magnetic geometry is further investigated using a time-dependent probability density function (PDF) model and information geometry to elucidate the roles played by pedestal plasma turbulence and perpendicular velocity flows. The degree of stochasticity of the plasma turbulence is observed to be sensitive to the plasma heating rate. The calculated square of the information rate shows changes in the relative density fluctuations and perpendicular velocity PDFs begin 2–5 ms prior to the L–H transition for three plasmas; providing a crucial measurement of the dynamic timescale of external transport barrier formation. Additionally, both information length and rate provide potential predictors of the L–H transition for these plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗

Frequency-domain vs time-domain SP{sub N} equations to simulate neutron noise

Inside the reactor core mechanical vibrations of fuel assemblies can produce high fluctuations around a steady-state configuration, known as neutron noise. This effect can cause the triggering of power reduction measures. Classically, diffusion theory has been used to simulate this behavior. However, this equation has some limitations if the materials of the reactor have strong variations. In this work, we use the diffusive time-dependent simplified spherical harmonics equations that improve the previous results without the necessity of using high computational requirements. In particular, two types of analyses with these equations (SP{sub 3}) are made: a frequency-domain and a time-domain. A numerical neutron noise benchmark tests the methodology and compare both formulations. First, numerical results show a good agreement between the amplitudes and phases of the SP3 equations computed with the frequency-domain and time-domain. Therefore, as the frequency-domain computation only requires to solve a linear system, it is a recommendable option for neutron noise computations. Second, one can conclude that for this type of nuclear systems, where the assemblies are not homogenized, the SP{sub 3} approximation results improve considerably the accuracy of the diffusion theory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Quantum Versus Classical Switching Dynamics of Driven Dissipative Kerr Resonators

Here, we report a first-principles study of the driven dissipative dynamics for Kerr oscillators in the mesoscopic regime. This regime is characterized by large Kerr nonlinearity, realized here using the nonlinear kinetic inductance of a large array of Josephson junctions. The experimentally measured nonlinear resonance lineshapes of the junction array modes show significant deviations from steady-state numerical predictions, and necessitate time-dependent numerical simulations indicative of strong measurement-induced dephasing in the system arising from the large cross-Kerr effect between array modes. Analytical and numerical calculations of switching rate corroborate this by showing the emergence of a slow time scale, which is much longer than the linear decay rate and is set by fluctuation-induced switching times in the bistable regime. Furthermore, our analysis shows that the usual quantum-activated escape treatment is inadequate for prediction of the switching rates at large frequency shifts caused by strong nonlinearities, necessitating a quantum treatment that utilizes the full system Liouvillian. Based on our analysis, we identify a universal crossover parameter that delineates the regimes of validity of semiclassical and quantum descriptions, respectively. Our work shows how dynamical switching effects in strongly nonlinear systems provide a platform to study quantum-to-classical transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Temporal Variability in Reservoir Surface Area Is an Important Source of Uncertainty in GHG Emission Estimates

Ebullitive methane (CH 4 ) emissions in lentic ecosystems tend to concentrate at river-lake interfaces and within shallow littoral zones. However, inconsistent definitions of the littoral zone and static representations of the lake or reservoir surface area contribute to major uncertainties in greenhouse gas (GHG) emissions estimates, particularly in reservoirs with large water-level fluctuations. This study examines temporal variation in littoral and total surface areas of US reservoirs and demonstrates how different methods and data sources lead to discrepencies in reservoir GHG emissions at large scales and over time. We also explore variability in remotely sensed water occurrence according to maximum surface area, reservoir purposes, and hydrologic regions. Notably, the largest relative variability in surface area is exhibited by small reservoirs with a maximum surface area <1 km 2 and non-hydroelectric reservoirs. Additionally, we use a case study of measured CH 4 emissions from the southeastern United States (Douglas Reservoir) to illustrate the effects of varying surface area on reservoir-wide GHG estimates. Upscaled CH 4 emissions in Douglas Reservoir differed by nearly two-fold depending on the source of total surface area data and whether estimates accounted for seasonal fluctuations in surface area. During seasonal drawdown in Douglas Reservoir, relative littoral area varies non-linearly; periods of lower pool elevation (and thus larger relative littoral area) likely contribute disproportionately high CH 4 emission rates compared to the commonly sampled summer season when water levels are at full-pool elevation. Improved GHG monitoring and upscaling techniques require accounting for temporal variability in reservoir surface extent and littoral area.

54 ENVIRONMENTAL SCIENCES↗

Local aging effects in PuB 4 : Growing inhomogeneity and slow dynamics of local field fluctuations probed by 239 Pu NMR

Plutonium-based correlated electron materials host exotic physical phenomena ranging from unconventional heavy-fermion superconductivity to topological Kondo insulating states. Self-irradiation damage can influence many properties of such radioactive materials. Structural disorder effects due to α radiation have been frequently studied using techniques such as transport, thermodynamics, and x-ray diffraction. Here, in this study, we use 239 Pu nuclear magnetic resonance (NMR) to study the long-term influence of self-damage on the lattice and local electronic structures in a single crystal of the candidate topological insulator plutonium tetraboride (PuB 4 ). We first characterize the anisotropy of the 239 Pu resonance and confirm the local axial-site symmetry inferred from previous polycrystalline measurements. Aging effects are then evaluated over the time frame of six years. We find that, though the static 239 Pu NMR spectra show a slight modulation in their shape, their field-rotation pattern reveals no change in 239 Pu local site symmetry over time, suggesting that aging has a surprisingly small impact on the spatial distribution of the static hyperfine field. Further, ligand-site 11 B NMR finds little time-dependent change in the size of electric field gradient around 11 B sites. By contrast, aging has a prominent impact on the 239 Pu NMR relaxation processes and signal intensity. Specifically, aging-induced damage manifests itself as an increase in the spin-lattice relaxation time 𝑇 1 , an increased distribution of 𝑇 1 , and a signal intensity that decreases linearly by 20% per year. An effective spin-spin relaxation time 𝑇 2,eff in the aged sample shortens drastically towards lower temperature, suggesting growth of slow fluctuations of the hyperfine field that are linked to radiation-damage-induced inhomogeneity. Our NMR study sheds light on the interplay of radiation damage and local magnetic interactions in correlated insulators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

JWST Noise Floor. II. Systematic Error Sources in JWST NIRCam Time Series

The James Webb Space Telescope (JWST) holds great promise for characterizing atmospheres of transiting exoplanets, potentially providing insights into Earth-sized planets within the habitable zones of M-dwarf host stars if photon-limited performance can be achieved. Here, we discuss the systematic error sources that are expected to be present in grism time-series observations with the NIRCam instrument. We find that pointing jitter and high-gain antenna moves in addition to the detectors’ subpixel crosshatch patterns will produce relatively small variations (less than 6 parts per million, ppm). The time-dependent aperture losses due to thermal instabilities in the optics can also be kept to below 2 ppm. To achieve these low noise values, it is important to employ a sufficiently large (more than 11) extraction aperture. Persistence due to charge-trapping will have a minor (less than 3 ppm) effect on the time series 20 minutes into an exposure and is expected to play a much smaller role than it does for the Hubble Space Telescope WFC3 detectors. We expect detector temperature fluctuations to contribute less than 3 ppm. In total, our estimated noise floor from known systematic error sources is only 9 ppm per visit. We urge caution, however, because unknown systematic error sources could be present in flight and will only be measurable on astrophysical sources such as quiescent stars. We find that reciprocity failure may introduce a perennial instrument offset at the 40 ppm level, so corrections may be needed when a multi-instrument multi-observatory spectrum is stitched together over wide wavelength ranges.

47 OTHER INSTRUMENTATION↗

From magnetic order to quantum disorder in the Zn-barlowite series of S = 1/2 kagomé antiferromagnets

We report a comprehensive muon spectroscopy study of the Zn-barlowite series of $S=\frac{1}{2}$ kagomé antiferromagnets, Zn x Cu 4-x (OH) 6 FBr, for x= 0.00 to 0.99(1). By combining muon spin relaxation and rotation measurements with state-of-the-art density-functional theory muon-site calculations, we observe the formation of both μ–F and μ–OH complexes in Zn-barlowite. From these stopping sites, implanted muon spins reveal the suppression of long-range magnetic order into a possible quantum spin liquid state upon the increasing concentration of Zn-substitution. In the parent compound (x = 0), static long-range magnetic order below T N = 5 K manifests itself in the form of spontaneous oscillations in the time-dependent muon asymmetry signal consistent with the dipolar fields expected from the calculated muon stopping sites and the previously determined magnetic structure of barlowite. Meanwhile, in the x = 1.0 end-member of the series—in which antiferromagnetic kagomé layers of Cu 2+ $S=\frac{1}{2}$ moments are decoupled by diamagnetic Zn 2+ ions—we observe that dynamic magnetic moment fluctuations persist down to at least 50 mK, indicative of a quantum disordered ground state. We demonstrate that this crossover from a static to dynamic magnetic ground state occurs for compositions of Zn-barlowite with x > 0.5, which bears resemblance to the dynamical behaviour of the widely studied Zn-paratacamite series that contains the quantum spin liquid candidate herbertsmithite.

36 MATERIALS SCIENCE↗

Kondo interaction of quantum spin Hall edge channels with charge puddles

Under time-reversal symmetry, quantum spin Hall edge channels are protected against elastic backscattering. However, even for samples which exhibit conductance quantization due to the quantum spin Hall effect, reproducible fluctuations shape the quantization plateau when the chemical potential is tuned through the bulk gap. Here, we examine those fluctuations in micron-sized HgTe quantum well devices. By performing temperature- and gate-dependent measurements, we conclude that “charge puddles” in the narrow-gap material have a Kondo-type interaction with the edge channels resulting in the observed conductance fluctuations. Our results provide insight into the underlying mechanisms of scattering in quantum spin Hall edge channels.

36 MATERIALS SCIENCE↗

Revisiting superconductivity in the extended one-band Hubbard model: Pairing via spin and charge fluctuations

The leading superconducting instabilities of the two-dimensional extended repulsive one-band Hubbard model within spin-fluctuation pairing theory depend sensitively on electron density, band, and interaction parameters. We map out the phase diagrams within a random-phase-approximation spin- and charge-fluctuation approach, and find that while B 1g (d x 2 –y 2 ) and B 2g (d xy ) pairing dominates in the absence of repulsive longer-range Coulomb interactions V NN , the latter induces pairing in other symmetry channels, including, e.g., A 2g (g-wave), nodal A 1g (extended s-wave), or nodal E u (p-wave) spin-triplet superconductivity. At the lowest temperatures, transition boundaries in the phase diagrams between symmetry-distinct spin-singlet orders generate complex time-reversal symmetry broken superpositions. By contrast, we find that boundaries between singlet and triplet regions are characterized by first-order transitions. Finally, motivated by recent photoemission experiments, we have determined the influence of an additional explicitly attractive nearest-neighbor interaction, V NN < 0, on the superconducting gap structure. Furthermore, depending on the electronic filling, such an attraction boosts E u (p-wave) spin-triplet or B 1g (d x 2 –y 2 ) spin-singlet ordering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Higher-order symmetry plane correlations in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

The correlations between event-by-event fluctuations of symmetry planes are measured in Pb-Pb collisions at a center-of-mass energy per nucleon pair $\sqrt{s_{NN}}$ = 5.02 TeV recorded by the ALICE detector at the Large Hadron Collider. This analysis is conducted using the Gaussian estimator technique, which is insensitive to biases from correlations between different flow amplitudes. The study presents, for the first time, the centrality dependence of correlations involving up to five different symmetry planes. The correlation strength varies depending on the harmonic order of the symmetry plane and the collision centrality. Comparisons with measurements from lower energies indicate no significant differences within uncertainties. Additionally, the results are compared with hydrodynamic model calculations. Although the model predictions provide a qualitative explanation of the experimental results, they overestimate the data for some observables. This is particularly true for correlators that are sensitive to the nonlinear response of the medium to initial-state anisotropies in the collision system. As these new correlators provide unique information—independent of flow amplitudes—their usage in future model developments can further constrain the properties of the strongly interacting matter created in ultrarelativistic heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Seasonality and longer-term development generate temporal dynamics in the Populus microbiome

ABSTRACT Temporal variation in community composition is central to our understanding of the assembly and functioning of microbial communities, yet the controls over temporal dynamics for microbiomes of long-lived plants, such as trees, remain unclear. Temporal variation in tree microbiomes could arise primarily from seasonal (i.e., intra-annual) fluctuations in community composition or from longer-term changes across years as host plants age. To test these alternatives, we experimentally isolated temporal variation in plant microbiome composition using a common garden and clonally propagated plants, and we used amplicon sequencing to characterize bacterial/archaeal and fungal communities in the leaf endosphere, root endosphere, and rhizosphere of two Populus spp. over four seasons across two consecutive years. Microbial community composition differed among seasons and years (which accounted for up to 21% of the variation in microbial community composition) and was correlated with seasonal dissimilarity in climatic conditions. However, microbial community dissimilarity was also positively correlated with time, reflecting longer-term compositional shifts as host trees aged. Together, our findings demonstrate that temporal patterns in tree microbiomes arise from both seasonal fluctuations and longer-term changes, which interact to generate unique seasonal patterns each year. In addition to shedding light on two important controls over the assembly of plant microbiomes, our results also suggest future studies of tree microbiomes should account for background temporal dynamics when testing the drivers of spatial patterns in microbial community composition and temporal responses of plant microbiomes to environmental change. IMPORTANCE Microbiomes are integral to the health of host plants, but we have a limited understanding of the factors that control how the composition of plant microbiomes changes over time. Especially little is known about the microbiome of long-lived trees, relative to annual and non-woody plants. We tested how tree microbiomes changed between seasons and years in poplar (genus Populus ), which are widespread and ecologically important tree species that also serve as important biofuel feedstocks. We found the composition of bacterial, archaeal, and fungal communities differed among seasons, but these seasonal differences depended on year. This dependence was driven by longer-term changes in microbial composition as host trees developed across consecutive years. Our findings suggest that temporal variation in tree microbiomes is driven by both seasonal fluctuations and longer-term (i.e., multiyear) development.

59 BASIC BIOLOGICAL SCIENCES↗

Thermodynamics and collisionality in firehose-susceptible high- β plasmas

We study the evolution of collisionless plasmas that, due to their macroscopic evolution, are susceptible to the firehose instability, using both analytic theory and hybrid-kinetic particle-in-cell simulations. We establish that, depending on the relative magnitude of the plasma β, the characteristic time scale of macroscopic evolution and the ion-Larmor frequency, the saturation of the firehose instability in high-β plasmas can result in three qualitatively distinct thermodynamic (and electromagnetic) states. By contrast with the previously identified ‘ultra-high-beta’ and ‘Alfvén-inhibiting’ states, the newly identified ‘Alfvén-enabling’ state, which is realised when the macroscopic evolution time τ exceeds the ion-Larmor frequency by a β-dependent critical parameter, can support linear Alfvén waves and Alfvénic turbulence because the magnetic tension associated with the plasma’s macroscopic magnetic field is never completely negated by anisotropic pressure forces. We characterise these states in detail, including their saturated magnetic-energy spectra. The effective collision operator associated with the firehose fluctuations is also described; we find it to be well approximated in the Alfvén-enabling state by a simple quasi-linear pitch-angle scattering operator. The box-averaged collision frequency is ν eff ∼ β/τ, in agreement with previous results, but certain subpopulations of particles scatter at a much larger (or smaller) rate depending on their velocity in the direction parallel to the magnetic field. Our findings are essential for understanding low-collisionality astrophysical plasmas including the solar wind, the intracluster medium of galaxy clusters and black hole accretion flows. We show that all three of these plasmas are in the Alfvén-enabling regime of firehose saturation and discuss the implications of this result.

astrophysical plasmas↗

The nanocaterpillar's random walk: diffusion with ligand–receptor contacts

Particles with ligand–receptor contacts bind and unbind fluctuating “legs” to surfaces, whose fluctuations cause the particle to diffuse. Quantifying the diffusion of such “nanoscale caterpillars” is a challenge, since binding events often occur on very short time and length scales. Here, in this work, we derive an analytical formula, validated by simulations, for the long time translational diffusion coefficient of an overdamped nanocaterpillar, under a range of modeling assumptions. We demonstrate that the effective diffusion coefficient, which depends on the microscopic parameters governing the legs, can be orders of magnitude smaller than the background diffusion coefficient. Furthermore it varies rapidly with temperature, and reproduces the striking variations seen in existing data and our own measurements of the diffusion of DNA-coated colloids. Our model gives insight into the mechanism of motion, and allows us to ask: when does a nanocaterpillar prefer to move by sliding, where one leg is always linked to the surface, and when does it prefer to move by hopping, which requires all legs to unbind simultaneously? We compare a range of systems (viruses, molecular motors, white blood cells, protein cargos in the nuclear pore complex, bacteria such as Escherichia coli, and DNA-coated colloids) and present guidelines to control the mode of motion for materials design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗