69 research outputs found
Protein accumulation in the endoplasmic reticulum as a non-equilibrium phase transition
Several neurological disorders are associated with the aggregation of
aberrant proteins, often localized in intracellular organelles such as the
endoplasmic reticulum. Here we study protein aggregation kinetics by mean-field
reactions and three dimensional Monte carlo simulations of diffusion-limited
aggregation of linear polymers in a confined space, representing the
endoplasmic reticulum. By tuning the rates of protein production and
degradation, we show that the system undergoes a non-equilibrium phase
transition from a physiological phase with little or no polymer accumulation to
a pathological phase characterized by persistent polymerization. A combination
of external factors accumulating during the lifetime of a patient can thus
slightly modify the phase transition control parameters, tipping the balance
from a long symptomless lag phase to an accelerated pathological development.
The model can be successfully used to interpret experimental data on
amyloid-\b{eta} clearance from the central nervous system
A network model for field and quenched disorder effects in artificial spin ice
We have performed a systematic study of the effects of field strength and
quenched disorder on the driven dynamics of square artificial spin ice. We
construct a network representation of the configurational phase space, where
nodes represent the microscopic configurations and a directed link between node
i and node j means that the field may induce a transition between the
corresponding configurations. In this way, we are able to quantitatively
describe how the field and the disorder affect the connectedness of states and
the reversibility of dynamics. In particular, we have shown that for optimal
field strengths, a substantial fraction of all states can be accessed using
external driving fields, and this fraction is increased by disorder. We discuss
how this relates to control and potential information storage applications for
artificial spin ices
Frustration and thermalization in an artificial magnetic quasicrystal
Artificial frustrated systems offer a playground to study the emergent properties of interacting systems. Most work to date has been on spatially periodic systems, known as artificial spin ices when the interacting elements are magnetic. Here we have studied artificial magnetic quasicrystals based on quasiperiodic Penrose tiling patterns of interacting nanomagnets. We construct a low-energy configuration from a step-by-step approach that we propose as a ground state. Topologically induced emergent frustration means that this configuration cannot be constructed from vertices in their ground states. It has two parts, a quasi-one-dimensional ‘skeleton’ that spans the entire pattern and is capable of long-range order, surrounding ‘flippable’ clusters of macrospins that lead to macroscopic degeneracy. Magnetic force microscopy imaging of Penrose tiling arrays revealed superdomains that are larger for more strongly coupled arrays, especially after annealing the array above its blocking temperature
Dynamics and hysteresis in square lattice artificial spin-ice
Dynamical effects under geometrical frustration are considered in a model for
artificial spin ice on a square lattice in two dimensions. Each island of the
spin ice has a three-component Heisenberg-like dipole moment subject to shape
anisotropies that influence its direction. The model has real dynamics,
including rotation of the magnetic degrees of freedom, going beyond the
Ising-type models of spin ice. The dynamics is studied using a Langevin
equation solved via a second order Heun algorithm. Thermodynamic properties
such as the specific heat are presented for different couplings. A peak in
specific heat is related to a type of melting-like phase transition present in
the model. Hysteresis in an applied magnetic field is calculated for model
parameters where the system is able to reach thermodynamic equilibrium.Comment: Revised versio
Disorder strength and field-driven ground state domain formation in artificial spin ice: experiment, simulation and theory
Quenched disorder affects how non-equilibrium systems respond to driving. In
the context of artificial spin ice, an athermal system comprised of
geometrically frustrated classical Ising spins with a two-fold degenerate
ground state, we give experimental and numerical evidence of how such disorder
washes out edge effects, and provide an estimate of disorder strength in the
experimental system. We prove analytically that a sequence of applied fields
with fixed amplitude is unable to drive the system to its ground state from a
saturated state. These results should be relevant for other systems where
disorder does not change the nature of the ground state.Comment: The manuscript has been reworked. To be published in Phys. Rev. Let
On thermalization of magnetic nano-arrays at fabrication
We propose a model to predict and control the statistical ensemble of
magnetic degrees of freedom in Artificial Spin Ice (ASI) during thermalized
adiabatic growth. We predict that as-grown arrays are controlled by the
temperature at fabrication and by their lattice constant, and that they can be
described by an effective temperature. If the geometry is conducive to a phase
transition, then the lowest temperature phase is accessed in arrays of lattice
constant smaller than a critical value, which depends on the temperature at
deposition. Alternatively, for arrays of equal lattice constant, there is a
temperature threshold at deposition and the lowest temperature phase is
accessed for fabrication temperatures {\it larger rather than smaller} than
this temperature threshold. Finally we show how to define and control the
effective temperature of the as-grown array and how to measure critical
exponents directly. We discuss the role of kinetics at the critical point, and
applications to experiments, in particular to as-grown thermalized square ASI,
and to magnetic monopole crystallization in as-grown honeycomb ASI.Comment: 14 pages, 2 figures. A theoretical approach to experimental results
reported in: Morgan J P, Stein A, Langridge S and Marrows C (2010) Nature
Physics 7 7
Extensive degeneracy, Coulomb phase and magnetic monopoles in an artificial realization of the square ice model
Artificial spin ice systems have been introduced as a possible mean to
investigate frustration effects in a well-controlled manner by fabricating
lithographically-patterned two-dimensional arrangements of interacting magnetic
nanostructures. This approach offers the opportunity to visualize
unconventional states of matter, directly in real space, and triggered a wealth
of studies at the frontier between nanomagnetism, statistical thermodynamics
and condensed matter physics. Despite the strong efforts made these last ten
years to provide an artificial realization of the celebrated square ice model,
no simple geometry based on arrays of nanomagnets succeeded to capture the
macroscopically degenerate ground state manifold of the corresponding model.
Instead, in all works reported so far, square lattices of nanomagnets are
characterized by a magnetically ordered ground state consisting of local
flux-closure configurations with alternating chirality. Here, we show
experimentally and theoretically, that all the characteristics of the square
ice model can be observed if the artificial square lattice is properly
designed. The spin configurations we image after demagnetizing our arrays
reveal unambiguous signatures of an algebraic spin liquid state characterized
by the presence of pinch points in the associated magnetic structure factor.
Local excitations, i.e. classical analogues of magnetic monopoles, are found to
be free to evolve in a massively degenerated, divergence-free vacuum. We thus
provide the first lab-on-chip platform allowing the investigation of collective
phenomena, including Coulomb phases and ice-like physics.Comment: 26 pages, 10 figure
Fluctuations in Protein Aggregation: Design of Preclinical Screening for Early Diagnosis of Neurodegenerative Disease
Autocatalytic fibril nucleation has recently been proposed to be a determining factor for the spread of neurodegenerative diseases, but the same process could also be exploited to amplify minute quantities of protein aggregates in a diagnostic context. Recent advances in microfluidic technology allow the analysis of protein aggregation in micron-scale samples, potentially enabling such diagnostic approaches, but the theoretical foundations for the analysis and interpretation of such data are, so far, lacking. Here, we study computationally the onset of protein aggregation in small volumes and show that the process is ruled by intrinsic fluctuations whose volume-dependent distribution we also estimate theoretically. Based on these results, we develop a strategy to quantify in silico the statistical errors associated with the detection of aggregate-containing samples. Our work explores a different perspective on the forecasting of protein aggregation in asymptomatic subjects
Metamaterial architecture from a self-shaping carnivorous plant
As meticulously observed and recorded by Darwin, the leaves of the carnivorous plant Drosera capensis L. slowly fold around insects trapped on their sticky surface in order to ensure their digestion. While the biochemical signaling driving leaf closure has been associated with plant growth hormones, how mechanical forces actuate the process is still unknown. Here, we combine experimental tests of leaf mechanics with quantitative measurements of the leaf microstructure and biochemistry to demonstrate that the closure mechanism is programmed into the cellular architecture of D. capensis leaves, which converts a homogeneous biochemical signal into an asymmetric response. Inspired by the leaf closure mechanism, we devise and test a mechanical metamaterial, which curls under homogeneous mechanical stimuli. This kind of metamaterial could find possible applications as a component in soft robotics and provides an example of bio-inspired design
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