383 research outputs found
Long-range effects in granular avalanching
We introduce a model for granular flow in a one-dimensional rice pile that
incorporates rolling effects through a long-range rolling probability for the
individual rice grains proportional to , being the distance
traveled by a grain in a single topling event. The exponent controls the
average rolling distance. We have shown that the crossover from power law to
stretched exponential behaviors observed experimentally in the granular
dynamics of rice piles can be well described as a long-range effect resulting
from a change in the transport properties of individual grains. We showed that
stretched exponential avalanche distributions can be associated with a
long-range regime for where the average rolling distance grows as a
power law with the system size, while power law distributions are associated
with a short range regime for , where the average rolling distance is
independent of the system size.Comment: 5 pages, 3 figure
Evolution of avalanche conducting states in electrorheological liquids
Charge transport in electrorheological fluids is studied experimentally under
strongly nonequlibrium conditions. By injecting an electrical current into a
suspension of conducting nanoparticles we are able to initiate a process of
self-organization which leads, in certain cases, to formation of a stable
pattern which consists of continuous conducting chains of particles. The
evolution of the dissipative state in such system is a complex process. It
starts as an avalanche process characterized by nucleation, growth, and thermal
destruction of such dissipative elements as continuous conducting chains of
particles as well as electroconvective vortices. A power-law distribution of
avalanche sizes and durations, observed at this stage of the evolution,
indicates that the system is in a self-organized critical state. A sharp
transition into an avalanche-free state with a stable pattern of conducting
chains is observed when the power dissipated in the fluid reaches its maximum.
We propose a simple evolution model which obeys the maximum power condition and
also shows a power-law distribution of the avalanche sizes.Comment: 15 pages, 6 figure
Mean Field Theory of Sandpile Avalanches: from the Intermittent to the Continuous Flow Regime
We model the dynamics of avalanches in granular assemblies in partly filled
rotating cylinders using a mean-field approach. We show that, upon varying the
cylinder angular velocity , the system undergoes a hysteresis cycle
between an intermittent and a continuous flow regimes. In the intermittent flow
regime, and approaching the transition, the avalanche duration exhibits
critical slowing down with a temporal power-law divergence. Upon adding a white
noise term, and close to the transition, the distribution of avalanche
durations is also a power-law. The hysteresis, as well as the statistics of
avalanche durations, are in good qualitative agreement with recent experiments
in partly filled rotating cylinders.Comment: 4 pages, RevTeX 3.0, postscript figures 1, 3 and 4 appended
Effect of Ordering on Spinodal Decomposition of Liquid-Crystal/Polymer Mixtures
Partially phase-separated liquid-crystal/polymer dispersions display highly
fibrillar domain morphologies that are dramatically different from the typical
structures found in isotropic mixtures. To explain this, we numerically explore
the coupling between phase ordering and phase separation kinetics in model
two-dimensional fluid mixtures phase separating into a nematic phase, rich in
liquid crystal, coexisting with an isotropic phase, rich in polymer. We find
that phase ordering can lead to fibrillar networks of the minority polymer-rich
phase
Internal avalanches in a pile of superconducting vortices
Using an array of miniature Hall probes, we monitored the spatiotemporal
variation of the internal magnetic induction in a superconducting niobium
sample during a slow sweep of external magnetic field. We found that a sizable
fraction of the increase in the local vortex population occurs in abrupt jumps.
The size distribution of these avalanches presents a power-law collapse on a
limited range. In contrast, at low temperatures and low fields, huge avalanches
with a typical size occur and the system does not display a well-defined
macroscopic critical current.Comment: 5 pages including 5 figure
Modeling relaxation and jamming in granular media
We introduce a stochastic microscopic model to investigate the jamming and
reorganization of grains induced by an object moving through a granular medium.
The model reproduces the experimentally observed periodic sawtooth fluctuations
in the jamming force and predicts the period and the power spectrum in terms of
the controllable physical parameters. It also predicts that the avalanche
sizes, defined as the number of displaced grains during a single advance of the
object, follow a power-law, , where the exponent is
independent of the physical parameters
Macroscopic Car Condensation in a Parking Garage
An asymmetric exclusion process type process, where cars move forward along a
closed road that starts and terminates at a parking garage, displays dynamic
phase transitions into two types of condensate phases where the garage becomes
macroscopically occupied. The total car density and the exit
probability are the two control parameters. At the transition, the
number of parked cars diverges in both cases, with the length of the road
, as with . Towards the transition, the
number of parked cars vanishes as with ,
or being the
distance from the transition. The transition into the normal phase represents
also the onset of transmission of information through the garage. This gives
rise to unusual parked car autocorrelations and car density profiles near the
garage, which depend strongly on the group velocity of the fluctuations along
the road.Comment: 12 pages including 15 figures; published version in PR
Dynamical mean-field approach to materials with strong electronic correlations
We review recent results on the properties of materials with correlated
electrons obtained within the LDA+DMFT approach, a combination of a
conventional band structure approach based on the local density approximation
(LDA) and the dynamical mean-field theory (DMFT). The application to four
outstanding problems in this field is discussed: (i) we compute the full
valence band structure of the charge-transfer insulator NiO by explicitly
including the p-d hybridization, (ii) we explain the origin for the
simultaneously occuring metal-insulator transition and collapse of the magnetic
moment in MnO and Fe2O3, (iii) we describe a novel GGA+DMFT scheme in terms of
plane-wave pseudopotentials which allows us to compute the orbital order and
cooperative Jahn-Teller distortion in KCuF3 and LaMnO3, and (iv) we provide a
general explanation for the appearance of kinks in the effective dispersion of
correlated electrons in systems with a pronounced three-peak spectral function
without having to resort to the coupling of electrons to bosonic excitations.
These results provide a considerable progress in the fully microscopic
investigations of correlated electron materials.Comment: 24 pages, 14 figures, final version, submitted to Eur. Phys. J. for
publication in the Special Topics volume "Cooperative Phenomena in Solids:
Metal-Insulator Transitions and Ordering of Microscopic Degrees of Freedom
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Soil microbiome signatures are associated with pesticide residues in arable landscapes
Pesticides are widely applied in agriculture to combat disease, pests, and weeds, leading to long-lasting contamination of agricultural soils with pesticide residues. While classical risk assessment experiments have repeatedly addressed immediate pesticide effects, we employ an ecological approach to investigate how pesticide residues persisting in soils influence the soil microbiome under realistic agricultural conditions. We assessed a wide range of soil characteristics, including the occurrence of 48 widely-used pesticides in 60 fields under conventional, no-tillage and organic management. We then tested which factors best explain soil microbiome traits. Environmental factors, including climate, geography, and soil characteristics, were the soil microbiome’s leading drivers. Remarkably, of all management factors, pesticide residues showed the strongest associations with soil microbiome traits, which were even more pronounced than the effects of cropping systems. Pesticide residues were almost exclusively positively associated with the relative abundance of 113 bacterial and 130 fungal taxa, many of them being assigned to taxa of known pesticide degraders. While fungal diversity and abundance were primarily positively associated with pesticide residues, bacterial diversity and abundance of the gene nifH - essential for biological nitrogen fixation - were negatively linked to the concentration of individual pesticide residues. Our results suggest that pesticide residues alter the soil microbiome, with potential long-term implications for the functioning of agricultural soils
Agricultural management and pesticide use reduce the functioning of beneficial plant symbionts
Phosphorus (P) acquisition is key for plant growth. Arbuscular mycorrhizal fungi (AMF) help plants acquire P from soil. Understanding which factors drive AMF-supported nutrient uptake is essential to develop more sustainable agroecosystems. Here we collected soils from 150 cereal fields and 60 non-cropped grassland sites across a 3,000 km trans-European gradient. In a greenhouse experiment, we tested the ability of AMF in these soils to forage for the radioisotope 33P from a hyphal compartment. AMF communities in grassland soils were much more efficient in acquiring 33P and transferred 64% more 33P to plants compared with AMF in cropland soils. Fungicide application best explained hyphal 33P transfer in cropland soils. The use of fungicides and subsequent decline in AMF richness in croplands reduced 33P uptake by 43%. Our results suggest that land-use intensity and fungicide use are major deterrents to the functioning and natural nutrient uptake capacity of AMF in agroecosystems.The Digging Deeper project was funded through the 2015-2016 BiodivERsA COFUND call for research proposals, with the national funders Swiss National Science Foundation (grant 31BD30-172466), Deutsche Forschungsgemeinschaft (317895346), Swedish Research Council Formas (contract 2016-0194), Ministerio de Economía y Competitividad (Digging_Deeper, Ref. PCIN-2016-028) and Agence Nationale de la Recherche (ANR, France; grant ANR-16-EBI3-0004-01)
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