Structure, Morphology, and Rheology of Polyelectrolyte Complex Hydrogels Formed by Self-Assembly of Oppositely Charged Triblock Polyelectrolytes
Abstract not provided
Srivastava, Samanvaya↗
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Catastrophic Cooling Instability in Optically Thin Plasmas
The solar corona is the prototypical example of a low-density environment heated to high temperatures by external sources. The plasma cools radiatively, and because it is optically thin to this radiation, it becomes possible to model the density, velocity, and temperature structure of the system by modifying the MHD equations to include an energy source term that approximates the local heating and cooling rates. The solutions can be highly inhomogeneous and even multiphase because the well-known linear instability associated with this source term, thermal instability, leads to a catastrophic heating and cooling of the plasma in the nonlinear regime. Here we show that there is a separate, much simpler linear instability accompanying this source term that can rival thermal instability in dynamical importance. The stability criterion is the isochoric one identified by Parker (1953), and we demonstrate that cooling functions derived from collisional ionization equilibrium are highly prone to violating this criterion. If catastrophic cooling instability can act locally in global simulations, then it is an alternative mechanism for forming condensations, and due to its nonequilibrium character, it may be relevant to explaining a host of phenomena associated with the production of cooler gas in hot, low density plasmas.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Kinetic Pathways to Diblock Copolymer Micelles via Thin Film Dissolution and Cosolvent Variation
We investigate how processing pathways control micelle formation during dissolution of lamellar diblock copolymers using dissipative particle dynamics (DPD) simulations and DPD-selfconsistent field theory (DPD-SCFT). Comparing thin film (TF) and cosolvent-assisted (CS) dissolution reveals fundamentally different micellization mechanisms and final states. In the TF pathway, dissolution proceeds through a metastable cylindrical intermediate that dictates final micelle dimensions. The lamellar melt first transforms into cylindrical micelles, which then fragment into spherical micelles. The final spherical radius is intrinsically linked to the cylinder radius by a constant ratio, Rsphere ≈ 1.4Rcylinder. DPD-SCFT confirms that both cylinders and spheres are near their equilibrium dimensions. In contrast, CS dissolution produces kinetically trapped micelles with sizes significantly below equilibrium. Micellization is hindered by high free energy barriers to single-chain exchange and fusion. Growth occurs primarily via fusion, but increasing corona repulsion suppresses further coarsening, preventing equilibration. These results demonstrate that, when starting from a bulk copolymer phase, the metastable cylindrical intermediate plays a central role in determining final micelle size.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Dynamic Phase Alignment in Inertial Alfvén Turbulence
In weakly collisional plasma environments with sufficiently low electron beta, Alfvénic turbulence transforms into inertial Alfvénic turbulence at scales below the electron skin depth, k ⊥ d e ≳ 1. We argue that, in inertial Alfvénic turbulence, both energy and generalized kinetic helicity exhibit direct cascades. We demonstrate that the two cascades are compatible due to the existence of a strong scale dependence of the phase alignment angle between velocity and magnetic field fluctuations, with the phase alignment angle scaling as cos α k ∝ $k$$^{–1}_{⊥}$. The kinetic and magnetic energy spectra scale as ∝ $k$$^{–5/3}_{⊥}$ and ∝ $k$$^{–11/3}_{⊥}$, respectively. As a result of the dual direct cascade, the generalized helicity spectrum scales as ∝ $k$$^{–5/3}_{⊥}$, implying progressive balancing of the turbulence as the cascade proceeds to smaller scales in the k ⊥ d e >> 1 range. Turbulent eddies exhibit a phase-space anisotropy k ∥ ∝ $k$$^{5/3}_{⊥}$, consistent with critically balanced inertial Alfvén fluctuations. Furthermore, our results may be applicable to a variety of geophysical, space, and astrophysical environments, including the Earth’s magnetosheath and ionosphere, solar corona, and nonrelativistic pair plasmas, as well as to strongly rotating nonionized fluids.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Hadronic resonance production and interaction in p-Pb collisions at LHC energies in EPOS3
Using the EPOS3 model with the Ultrarelativistic Quantum Molecular Dynamics (UrQMD) model to describe the hadronic phase, we study the production of short-lived hadronic resonances and the modification of their yields and p T spectra in p-Pb collisions at √sNN= 5.02 TeV. High-multiplicity p-Pb collisions exhibit similar behavior to midperipheral Pb-Pb collisions at LHC energies, and we find indications of a short-lived hadronic phase in p-Pb collisions that can modify resonance yields and p T spectra through scattering processes. The evolution of resonance production is investigated as a function of the system size, which is related to the lifetime of the hadronic phase in order to study the onset and evolution of scattering effects in p-Pb collisions. We also study hadron production separately in the core and corona parts of these collisions and explore how this division affects the total particle yields as the system size increases.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Dynamic Nanocrystal-Ligand Boundaries: Reversible Photoinduced Ligand Detachment from Quantum Dots in Solution
The porosity of ligand shells of colloidal quantum dots (QDs) can influence the overall rate and yield of charge transfer processes occurring at their surfaces. However, the density of ligand shells on QDs can also influence their colloidal and photochemical stability. We used time-resolved infrared spectroscopy to show that photoinduced ligand detachment, the tendency for certain ligands to detach from QD surfaces when the nanocrystals are promoted to their excitonic excited states, can be used to transiently enhance the porosity of oleic acidpassivated CdSe QDs in solution. Furthermore, we synthesized CdSe QDs with varying ligand shell densities to examine the corresponding influence that van der Waals interactions among ligands have on the yield of photoinduced ligand detachment and the time scale on which ligands return to QD surfaces. We observed that oleic acid ligands on CdSe QDs with lower shell densities have a higher probability of escape for longer periods of time. Despite this, oleic acid ligands on fully passivated CdSe QDs are still able to photodetach, resulting in a transient increase of their ligand shell porosity. In contrast, QDs with multilayer ligand coronas exhibit negligible photoinduced ligand detachment because the outer molecular layers introduce a type of cage effect, preventing the escape of the interior ligands. Our findings suggest the intriguing possibility that photoinduced ligand detachment can be used to transiently decrease the density of ligand shells of QDs to facilitate charge transfer processes while still allowing them to be fully passivated between excitation events for photochemical and colloidal stability.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Dynamic Phase Alignment in Inertial Alfven Turbulence
In weakly-collisional plasma environments with sufficiently low electron beta, Alfvenic turbulence transforms into inertial Alfvenic turbulence at scales below the electron skin-depth. We argue that, in inertial Alfvenic turbulence, both energy and generalized kinetic helicity exhibit direct cascades. We demonstrate that the two cascades are compatible due to the existence of a strong scale-dependence of the phase alignment angle between velocity and magnetic field fluctuations, with the phase alignment angle scaling as proportional to the perpendicular wavenumber to the power of -1. The kinetic and magnetic energy spectra scale as the perpendicular wavenumber to the power of -5/3 and -11/3, respectively. As a result of the dual direct cascade, the generalized-helicity spectrum scales as the perpendicular wavenumber to the power of -5/3, implying progressive balancing of the turbulence as the cascade proceeds to smaller scales in the sub-electron-skin-depth range. Turbulent eddies exhibit a phase-space anisotropy, with the parallel wavenumber scaling as the perpendicular wavenumber to the power of 5/3, consistent with critically-balanced inertial Alfven fluctuations. Our results may be applicable to a variety of geophysical, space, and astrophysical environments, including the Earth's magnetosheath and ionosphere, solar corona, non-relativistic pair plasmas, as well as to strongly rotating non-ionized fluids.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Identification of the weak-to-strong transition in Alfvénic turbulence from space plasma
Abstract Plasma turbulence is a ubiquitous dynamical process that transfers energy across many spatial and temporal scales in astrophysical and space plasma systems. Although the theory of anisotropic magnetohydrodynamic (MHD) turbulence has successfully described natural phenomena, its core prediction of an Alfvénic transition from weak to strong MHD turbulence when energy cascades from large to small scales has not been observationally confirmed. Here we report evidence for the Alfvénic weak-to-strong transition in small-amplitude, turbulent MHD fluctuations in Earth’s magnetosheath using data from four Cluster spacecraft. Our observations demonstrate the universal existence of strong turbulence accompanied by weak turbulent fluctuations on large scales. Moreover, we find that the nonlinear interactions of MHD turbulence are crucial to the energy cascade, as they broaden the cascade directions and fluctuating frequencies. The observed connection between weak and strong MHD turbulence systems may be present in many astrophysical environments, such as star formation, energetic particle transport, turbulent dynamos, and solar corona or solar wind heating.
79 ASTRONOMY AND ASTROPHYSICS↗
Identification of the weak-to-strong transition in Alfvénic turbulence from space plasma
Plasma turbulence is a ubiquitous dynamical process that transfers energy across many spatial and temporal scales in astrophysical and space plasma systems. Although the theory of anisotropic magnetohydrodynamic (MHD) turbulence has successfully described natural phenomena, its core prediction of an Alfvénic transition from weak to strong MHD turbulence when energy cascades from large to small scales has not been observationally confirmed. Here we report evidence for the Alfvénic weak-to-strong transition in small-amplitude, turbulent MHD fluctuations in Earth’s magnetosheath using data from four Cluster spacecraft. Our observations demonstrate the universal existence of strong turbulence accompanied by weak turbulent fluctuations on large scales. Moreover, we find that the nonlinear interactions of MHD turbulence are crucial to the energy cascade, as they broaden the cascade directions and fluctuating frequencies. The observed connection between weak and strong MHD turbulence systems may be present in many astrophysical environments, such as star formation, energetic particle transport, turbulent dynamos, and solar corona or solar wind heating.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Amantadine interactions with phase separated lipid membranes
Amantadine, a small amphilphic organic compound that consists of an adamantane backbone and an amino group, was first recognized as an antiviral in 1963 and received approval for prophylaxis against the type A influenza virus in 1976. Since then, it has also been used to treat Parkinson’s disease-related dyskinesia and is being considered as a treatment for corona viruses. Since amantadine usually targets membrane-bound proteins, its interactions with the membrane are also thought to be important. Biological membranes are now widely understood to be laterally heterogeneous and certain proteins are known to preferentially co-localize within specific lipid domains. Does amantadine, therefore, preferentially localize in certain lipid composition domains? To address this question, here, we studied amantadine’s interactions with phase separating membranes composed of cholesterol, DSPC (1,2-distearoyl-sn-glycero-3-phosphocholine), POPC (1-palmitoyl-2-oleoyl-glycero-3-phosphocholine), and DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine), as well as single-phase DPhPC (1,2-diphytanoyl-sn-glycero-3-phos-phocholine) membranes. From Langmuir trough and differential scanning calorimetry (DSC) measurements, we determined, respectively, that amantadine preferentially binds to disordered lipids, such as POPC, and lowers the phase transition temperature of POPC/DSPC/cholesterol mixtures, implying that amantadine increases membrane disorder. Further, using droplet interface bilayers (DIBs), we observed that amantadine disrupts DPhPC membranes, consistent with its disordering properties. Finally, we carried out molecular dynamics (MD) simulations on POPC/DSPC/cholesterol membranes with varying amounts of amantadine. Consistent with experiment, MD simulations showed that amantadine prefers to associate with disordered POPC-rich domains, domain boundaries, and lipid glycerol backbones. Since different proteins co-localize with different lipid domains, our results have possible implications as to which classes of proteins may be better targets for amantadine.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Operation at Reduced Atmospheric Pressure and Concept of Reliability Redundancy for Optimized Design of Insulation Systems
Electrified transportation is calling for insulation design criteria that is adequate to provide elevated levels of power density, power dynamics and reliability. Increasing voltage levels are expected to cause accelerated intrinsic and extrinsic aging effects which will not be easily predictable at the design stage due to a lack of suitable modeling. Designing reliable insulation systems would require finding solutions able to control accelerated aging due to an unpredictable increase of intrinsic stresses and the onset of extrinsic stresses as partial discharges. This paper proposes the concept of reliability redundancy for the insulation design of aerospace electrical asset components, which is also validated at lower-than-standard atmospheric pressure. The principle is that extrinsic-aging-free design might be achieved upon determining the aging stress or abnormal service stresses distribution and being sure that aging will not generate conditions that can incept extrinsic aging (partial discharges) during operation life. However, such information is never, in practice, fully available to insulation system designers. Hence, especially in critical applications such as electrified aircraft, aerospace, and combat ships a further level of reliability should be added to a partial-discharge-free design, which can consist of the use of corona-resistant materials and/or of life models able to consider the accelerated aging effect of partial discharges (or any other type of extrinsic-accelerated aging factor). Innovative life modeling considering both extrinsic and intrinsic aging stresses, insulating material testing to estimate model parameters, and a metric for quantifying the extent of corona (or partial discharge) resistance can lead to establishing feasibility and limit conditions for optimized or fully reliability-redundant design. It is shown in the paper that if an extrinsic-aging-free design is not feasible, and it is therefore replaced by a redundant design, a further level of reliability redundancy can be provided by effective condition monitoring plans.
Montanari, Gian Carlo↗
Accelerating kinetic plasma simulations with machine-learning-generated initial conditions
Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.
Artificial neural networks↗
Characterization of fast magnetosonic waves driven by compact toroid plasma injection along a magnetic field
Magnetosonic waves are low-frequency, linearly polarized magnetohydrodynamic (MHD) waves commonly found in space, responsible for many well-known features, such as heating of the solar corona. In this work, we report observations of interesting wave signatures driven by injecting compact toroid (CT) plasmas into a static Helmholtz magnetic field at the Big Red Ball Facility at Wisconsin Plasma Physics Laboratory. By comparing the experimental results with the MHD theory, we identify that these waves are the fast magnetosonic modes propagating perpendicular to the background magnetic field. Additionally, we further investigate how the background field, preapplied poloidal magnetic flux in the CT injector, and the coarse grid placed in the chamber affect the characteristics of the waves. Since this experiment is part of an ongoing effort of creating a target plasma with tangled magnetic fields as a novel fusion fuel for magneto-inertial fusion (MIF), our current results could shed light on future possible paths of forming such a target for MIF.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Kinetic mix at gas-shell interface in inverted corona fusion targets
Gas-filled, laser-driven “inverted corona” fusion targets have attracted interest as a low-convergence neutron source and platform for studying kinetic physics. At the fill pressures under investigation, ejected particles from the shell can penetrate deeply into the gas before colliding, leading to significant mixing across the gas–shell interface. Here, we use kinetic-ion, fluid-electron hybrid particle-in-cell simulations to explore the nature of that mix. Simulations of the system demonstrate characteristics of a weakly collisional electrostatic shock, whereby a strong electric field accelerates shell ions into the rarefied gas and reflects upstream gas ions. This interpenetration is mediated by collisional processes: At higher initial gas pressure, fewer shell particles pass into the mix region and reach the hotspot. This effect is detectable through neutron yield scaling vs gas pressure. Predictions of neutron yield scaling show excellent agreement with experimental data recorded at the OMEGA laser facility, suggesting that 1D kinetic mechanisms are sufficient to capture the mix process.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Flow and thermal modelling of the argon volume in the DarkSide-20k TPC
The DarkSide-20k dark matter experiment, currently under construction at LNGS, features a dual-phase time projection chamber (TPC) with a ∼ 50 t argon target from an underground well. At this scale, it is crucial to optimise the argon flow pattern for efficient target purification and for fast distribution of internal gaseous calibration sources with lifetimes of the order of hours. To this end, we have performed computational fluid dynamics simulations and heat transfer calculations. The residence time distribution shows that the detector is well-mixed on time-scales of the turnover time (∼ 40 d). Notably, simulations show that despite a two-order-of-magnitude difference between the turnover time and the half-life of 83m Kr of 1.83 h, source atoms have the highest probability to reach the centre of the TPC 13 min after their injection, allowing for a homogeneous distribution before undergoing radioactive decay. We further analyse the thermal aspects of dual-phase operation and define the requirements for the formation of a stable gas pocket on top of the liquid. We find a best-estimate value for the heat transfer rate at the liquid-gas interface of 62 W with an upper limit of 144 W and a minimum gas pocket inlet temperature of 89 K to avoid condensation on the acrylic anode. This study also informs the placement of liquid inlets and outlets in the TPC. The presented techniques are widely applicable to other large-scale, noble-liquid detectors.
47 OTHER INSTRUMENTATION↗
The root-zone soil moisture spectrum in a mediterranean ecosystem
Storage of water within soil pores of the root zone introduce memory effects in the dynamics of soil moisture that are considerably longer than the integral timescale of many atmospheric processes. Thus, hydro-climatic states can be “sustained” through land-surface heat and water vapor fluxes primarily because they can “feed off” on this long-term soil moisture memory. Root-zone soil moisture memory is only but one feature characterizing the spectrum of soil moisture dynamics, which is analyzed here using a combination of long-term measurements and models. In particular, the spectrum of root-zone soil moisture content in a Mediterranean ecosystem is examined using 14-years of half-hourly measurements. A distinguishing hydro-climatic feature in such ecosystems is that sources (mainly rainfall) and sinks (mainly evapotranspiration) of soil moisture are roughly out of phase with each other. For over 4 decades of time scales and 7 decades of energy, the canonical shape of the measured soil moisture spectrum is shown to be approximately Lorentzian determined by the soil moisture variance and its memory but with two exceptions: the occurrences of a peak at diurnal-to-daily time scales and a weaker peak at near annual time scales. Model calculations and spectral analysis demonstrate that diurnal and seasonal variations in hydroclimate forcing responsible for variability in evapotranspiration had minor impact on the normalized shape of the soil moisture spectrum. However, their impact was captured by adjustments in the temporal variance. These findings indicate that precipitation and not evapotranspiration variability dominates the multi-scaling properties of soil moisture variability consistent with prior climate model simulations. Furthermore, the soil moisture memory inferred by the annual peak of soil moisture (340 d) is consistent with climate model simulations, while the memory evaluated from the loss function of a linearized mass balance approach leads to a smaller value (50 d), highlighting the effect of weak non-stationarity on soil moisture variability.
54 ENVIRONMENTAL SCIENCES↗
Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission
NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.
54 ENVIRONMENTAL SCIENCES↗