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Phase transitions in cells provide a wonderful arena for investigation by students of physics, chemistry, and biology to come together to apply their foundational knowledge. In this article, we provide an intuitive approach to the basic physical principles of phase separation. We then highlight several examples that illustrate how the cell, the fundamental unit of life, makes use of phase separation to organise its contents. [ABSTRACT FROM AUTHOR]

With the advent of continuous direct compression (CDC) process, it becomes increasingly desirable to characterize inherent powder blend heterogeneity at a small batch scale for a robust and CDC-amenable formulation. To accomplish this goal, a near infrared spectroscopy (NIRS)-based characterization approach was developed and implemented on multiple direct compression (DC) blends in this study, with the intended purpose of complementing existing formulation development tools and enabling to build an early CMC data package for late-phased process analytical technology (PAT) method development. Three fumaric acid DC blends, designed to harbor varied degrees of inherent blend heterogeneity, were employed. Near infrared spectral data were collected on a kg-scale batch blender via both time- and angle-based triggering modes. The time-triggered data were used to investigate the blending heterogeneity with respect to rotation angles, while the angle-triggered data were used to provide blending variability characterization and compare against off-line HPLC-based results. The time-triggered data revealed that the greatest blend variability was observed between revolutions, while the blending variability within a single revolution stayed relatively low with respect to rotation angles. This confirmed earlier literature findings that the bottom layer of powder blends tends to move with the blender within each revolution, and the most intense powder mixing takes place across revolutions. This also indicates the use of blending speed and the number of co-adds are not able to increase sampling volume to improve signal-to-noise ratio under a tumble-bin blender as what were typically done in a feedframe application. The angle-triggered data showed that there is a consistent trend between NIRS and HPLC-based methods on characterizing blend heterogeneity across the blends at a given sample size. This study contributes to establishing NIRS as a potential characterization approach for inherent powder blend heterogeneity for early R&D. It also highlights the promise of continuous characterization of inherent powder blend heterogeneity from gram scale to mini-batch CDC scale. [ABSTRACT FROM AUTHOR]

Shear banding in entangled polymer solutions is an elusive phenomenon in polymer rheology. One recently proposed mechanism for the existence of banded velocity profiles in entangled polymer solutions stems from a coupling of the flow to banded concentration profiles. Recent work [Burroughs et al., Phys. Rev. Lett.126, 207801 (2021)] provided experimental evidence for the development of large gradients in concentration across the fluid. Here, a more systematic investigation is reported of the transient and steady-state banded velocity and concentration profiles of entangled polybutadiene in dioctyl phthalate solutions as a function of temperature (T) , number of entanglements (Z), and applied shear rate (W i a p p ), which control the susceptibility of the fluid to unstable flow-concentration coupling. The results are compared to a two-fluid model that accounts for coupling between elastic and osmotic polymer stresses, and a strong agreement is found between model predictions and measured concentration profiles. The interface locations and widths of the time-averaged, steady-state velocity profiles are quantified from high-order numerical derivatives of the data. At high levels of entanglement and large W i a p p , a significant wall slip is observed at both inner and outer surfaces of the flow geometry but is not a necessary criterion for a nonhomogeneous flow. Furthermore, the transient evolution of flow profiles for large Z indicate transitions from curved to "stair-stepped" and, ultimately, a banded steady state. These observed transitions provide detailed evidence for shear-induced demixing as a mechanism of shear banding in polymer solutions. [ABSTRACT FROM AUTHOR]

In this letter, we consider a novel problem of blind source separation from observed magnitude-only measurements of their convolutive mixture in different communication systems. The problem setups correspond to a blind receiver architecture that either does not have phase information in the measurements or has excessive phase noise that cannot be easily recovered. We have formulated the problem as a matrix recovery problem by using the lifting technique and proposed a convex programming-based solution for joint recovery of the unknown channel and source signals. We have implemented the proposed solution using the alternating direction method of multipliers (ADMM). We have plotted a phase transition diagram for random Gaussian subspaces that shows, for s source signals each of length n and channel of length k, the minimum measurements required for exact recovery are m ≥ 1.19 (s n + k) log 2 m that is in accord with our theoretical result. We have also plotted a phase transition diagram for the case where the channel delays matrix is deterministic (consisting of the first k columns of the identity matrix) that shows the minimum measurements required for exact recovery are m ≥ 2.86 (s n + k) log 2 m which are higher than random subspaces. [ABSTRACT FROM AUTHOR]

In dense biological tissues, cell types performing different roles remain segregated by maintaining sharp interfaces. To better understand the mechanisms for such sharp compartmentalization, we study the effect of an imposed heterotypic tension at the interface between two distinct cell types in a fully 3D Voronoi model for confluent tissues. We find that cells rapidly sort and self-organize to generate a tissue-scale interface between cell types, and cells adjacent to this interface exhibit signature geometric features including nematic-like ordering, bimodal facet areas, and registration, or alignment, of cell centers on either side of the two-tissue interface. The magnitude of these features scales directly with the magnitude of the imposed tension, suggesting that biologists can estimate the magnitude of tissue surface tension between two tissue types simply by segmenting a 3D tissue. To uncover the underlying physical mechanisms driving these geometric features, we develop two minimal, ordered models using two different underlying lattices that identify an energetic competition between bulk cell shapes and tissue interface area. When the interface area dominates, changes to neighbor topology are costly and occur less frequently, which generates the observed geometric features. [ABSTRACT FROM AUTHOR]

A mixed hyperbolic-parabolic, non conservative, Reynolds Stress Model (RSM), is studied. It is based on an underlying set of Langevin equations, and allows to describe turbulent mixing, including transient demixing effects as well as incomplete mixing. Its mathematical structure is analysed, and specific regimes, related to acoustic-like, Riemann-type, or self-similar solutions, are identified. A second-order accurate numerical scheme is proposed in arbitrary curvilinear geometry. Its accuracy and convergence behaviour are tested by comparison with analytical solutions in the different regimes. The numerical scheme can be generalized to multi-dimensional configurations, with potentially cylindrical symmetry, on unstructured meshes. [ABSTRACT FROM AUTHOR]

[Display omitted] • New methodology allows exploration of full formulation or phase diagram. • Mixing rules predict properties of binary and ternary mixtures. • Demixing rules predict properties of individual pure component powders. • Can be used to obtain parameters of materials that show poor tabletting. • Quantitative and qualitative agreement of compaction pressures and shear stresses. A set of numerical methods is described that allows predictive finite element method (FEM) simulations of the compaction of multi-component pharmaceutical powder formulations across the entire range of compositions. An automated parametrisation procedure was used to extract density-dependent Drucker-Prager Cap (dDPC) model parameters from experimental data. Subsequently, these parameters were interpolated (mixed) or extrapolated (demixed) to predict dDPC model parameters of unseen powder formulations. Pure, binary, and ternary formulations of micro-crystalline cellulose (MCC, plastic), dibasic calcium phosphate dihydrate (DCPD, brittle), and pre-gelatinised starch (STA, elastic) powders were used to validate the parametrisation and mixing/demixing methodologies. FEM simulations were capable of reproducing compaction curves with errors only marginally greater than the experimental variability. Using only pure component data, FEM simulations with mixing rules were capable of predicting the compaction curves of mixtures as well as their shear stress distributions. Moreover, with data of only two or three powder formulations, a new demixing methodology was able to predict the behaviour of the constituent powders. The combination of these methodologies provides a powerful tool to rapidly explore powder formulations anywhere within the composition phase diagram, providing compaction curves but also stress profiles that are essential to early-stage formulation process development and tooling design. [ABSTRACT FROM AUTHOR]

Blind deconvolution and demixing is the problem of reconstructing convolved signals and kernels from the sum of their convolutions. This problem arises in many applications, such as blind MIMO. This work presents a separable approach to blind deconvolution and demixing via convex optimization. Unlike previous works, our formulation allows separation into smaller optimization problems, which significantly improves complexity. We develop recovery guarantees, which comply with those of the original non-separable problem, and demonstrate the method performance under several normalization constraints. [ABSTRACT FROM AUTHOR]

Processing of concentrated lignocellulosic biomass suspensions typically involves the conversion of the cellulose into sugars and sugars into ethanol. Biomass is usually pretreated via methods like comminution or steam explosion to form fine cellulosic fibers to be dispersed into an aqueous phase for further treatment. The resulting cellulose suspensions need to be pressurized and pumped into and out of various processing vessels without allowing the development of flow instabilities that are typically associated with "demixing", that is, the segregation of the cellulosic biomass from the aqueous phase via the formation of mats of cellulosic fibers and the filtration of the aqueous phase. Such demixing can prevent continuous processing at high rates. Here, the development of flow instabilities via the demixing effect for cellulose suspensions is demonstrated using capillary and compressive squeeze flows. It is shown that the use of a gelation agent, hydroxypropyl guar gum, at the critical concentration of 0.5 wt% or higher significantly affects the viscoelastic material functions of cellulosic suspensions, improves the dispersive mixing of the fibers within the aqueous phase, and results in the elimination of the flow instabilities and associated demixing effects that are ubiquitously observed during the pressurization and processing of cellulosic suspensions. [ABSTRACT FROM AUTHOR]

In light of recent advancements in the constitutive modeling of bidisperse and polydisperse entangled linear polymers, we present a new "multifluid" generalization of the classic two-fluid approximation for flows of inhomogeneous polymer blends. As an application of the model, we consider predictions for the linear and nonlinear dynamics of shear induced demixing (SID) instabilities in blends with bidisperse and log-normal molecular weight distributions. We find that even in the absence of any chemical contrast between component chains, an imposed flow can induce a demixing instability provided there is sufficient contrast in the size of the two chains. The lower bound polydispersity for SID coincides with the point where elastic forces (k B T per entanglement) scaled by the contrast between chains (e.g., polydispersity index minus one) exceed the entropic forces for mixing (k B T per chain). For bidisperse blends, we show that the nonlinear dynamics of SID strongly resemble what has previously been shown for SID in entangled polymer solutions. [ABSTRACT FROM AUTHOR]

Consistent estimators of the mixing distribution in Poisson mixture models are con- structed for both the right censored and the uncensored case. The estimators are based on a kind of Laplace inversion via factorial moments. The rate of convergence of the mean integrated squared error of these estimators is (log n= log log n)2. It is also shown that there do not exist estimators for which this rate is better. [ABSTRACT FROM AUTHOR]

An argon-helium free-burning arc that operates on a graphite anode is investigated. Images of the arc and anode attachment under different arc currents and different helium ratios are exhibited. Experimental results show that both the arc and anode attachment are characterized by demixing. Moreover, an annular dark region surrounding the anode center is observed in the anode attachment region under the conditions of a higher arc current and a higher helium ratio, which is similar to the self-organized anode attachment mode in glow discharges. Preliminary analysis indicates that the arc demixing, the thermophysical properties of the mixture gas, and the carbon vapors from anode evaporation contribute to the formation of this novel anode attachment mode. • Both arc and anode attachment are characterized by demixing. • Annular dark region on the anode appears under high arc current and high helium ratio. • Anode attachment with annular dark region may be a self-organized mode. • Carbon vapors from anode evaporation promote the formation of annular dark region. [ABSTRACT FROM AUTHOR]

A Gaussian mixed fractional process { Y (t) } t ∈ R = { P X (t) } t ∈ R is a multivariate stochastic process obtained by pre-multiplying a vector of independent, Gaussian fractional process entries X by a nonsingular matrix P. It is interpreted that Y is observable, while X is a hidden process occurring in an (unknown) system of coordinates P. Mixed processes naturally arise as approximations to solutions of physically relevant classes of multivariate fractional stochastic differential equations under aggregation. We propose a semiparametric two-step wavelet-based method for estimating both the demixing matrix P - 1 and the memory parameters of X. The asymptotic normality of the estimator is established both in continuous and discrete time. Monte Carlo experiments show that the estimator is accurate over finite samples, while being very computationally efficient. As an application, we model a bivariate time series of annual tree ring width measurements. [ABSTRACT FROM AUTHOR]

In the present paper, we continue our recent studies on a two-fluid Rolie-Poly approximation of entangled polymer solutions in simple shear flows. We review the existing literature on shear induced demixing (SID) in two-fluid models and highlight the apparent similarities to a thermodynamic model of demixing. Focusing on steady unidirectional simple shear flows driven by a constant applied shear stress, we show that when the frictional drag between solvent and polymer is asymptotically large, our two-fluid model is mathematically equivalent to a thermodynamic model in terms of its long-time concentration dynamics. In particular, we show that SID minimizes a Lyapunov functional L distinct from the system's free energy F. We apply our asymptotic model to make predictions regarding nucleation (finite amplitude instabilities) and coalescence phenomena in SID. Numerical calculations with the full model corroborate the asymptotic model predictions. Finally, we apply the same asymptotic analysis to two flows in which a thermodynamic mapping fails. First, we consider steady simple shear flows driven by a constant boundary velocity (as opposed to a constant boundary stress), wherein the hydrodynamic instability appears to have the same character but can no longer be mapped to an equivalent thermodynamic instability. Second, we consider unsteady simple shear flows driven by an oscillating boundary stress, wherein the nonlinear dynamics of demixing are totally distinct from what a thermodynamic model predicts. [ABSTRACT FROM AUTHOR]

The decay of the Convective Boundary Layer (CBL) is studied using large-eddy simulations of free and advective CBLs, in which surface heat supply is suddenly cut off. After the cutoff, coherent convective circulations last about one convective time scale and then fade away. In the mixed layer, the decay time scale increases with height, indicating that nonlocal eddies decay slower than near-surface local eddies. The slower decay of turbulence in the middle of CBL than near-surface turbulence is reconfirmed from the analysis of pattern correlations of perturbations of vertical velocity. Perturbations of potential temperature and scalar concentration decay faster and slower than vertical velocity perturbations, respectively. A downward propagation of negative heat flux and its oscillation are found and a quadrant analysis reveals that warmer air sinking events are responsible for the downward propagation. The fourth quadrant events seem to be induced by demixing of air parcels, entrained from above the CBL. The advective CBL simulation with geostrophic wind illustrates that near-surface eddies are mechanically generated and they decelerate flow from the bottom up in the CBL/residual layer. The two-dimensional spectra show the height- and scale-dependent characteristics of decaying convective turbulence again in the free and advective boundary layer simulations.

Assume we are given a sum of linear measurements of s different rank-r matrices of the form y=∑k=1sAk(Xk). When and under which conditions is it possible to extract (demix) the individual matrices Xk from the single measurement vector y? And can we do the demixing numerically efficiently? We present two computationally efficient algorithms based on hard thresholding to solve this low rank demixing problem. We introduce an Amalgam-Restricted Isometry Property which is especially suitable for demixing problems and prove that under appropriate conditions these algorithms are guaranteed to converge to the correct solution at a linear rate. We discuss applications in connection with quantum tomography and the Internet-of-Things. Numerical simulations demonstrate the empirical performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Sodium adsorption ratio SAR defined as SAR = (Na) / V w(Ca+Mg)/2 here concentrations of cations in solution are expressed in meq/L has long been considered as correlated to exchangeable sodium percentage (ESP) on clay minerals or soil exchange complex, and as the key concept to explain swelling of clay minerals and the difficulties of reclaiming salt-affected soils. Though its basis is empirical, it was alleged to be theoretically justified on the basis of ion exchange, derived from the Gapon convention. However, it has long been challenged on the basis of both field observations and experimental evidence : it fails to account for the fact that calcium and magnesium do not play the same role, while potassium is absent from the formula ; calcium concentration must be “corrected “when calcite is present etc. There exist specific ion effects. Experimental measurements of the decrease of permeability when solutions are diluted led Quirk and Schofield (1955) to define the concept of critical threshold, and to show that potassium and magnesium play an intermediate role between sodium and calcium. This threshold is simply determined by the concentration of calcium, irrespective of the value of SAR or ESP. Indeed, demixing of Ca-Na clay minerals during ion exchange, a phenomenon well known since Glaeser and Mering (1954), implies that there exists an interaction between adjacent sites. This undermines the theoretical basis of SAR : the derivation of SAR from ion exchange equilibria implies to use an equilibrium constant. This parameter is no more constant if demixing occurs. The results obtained are positive : demixing leads to expulsion of sodium from inner exchange surfaces and its replacement by calcium, according to the “three crystals pore”proposed by Quirk (2003b). Sodium can then be more easily leached, as permeability is maintained by clusters of Ca-sites. Calcium concentration in solution appears thus as the simpler parameter to guide saltaffected soils reclamation when swelling clays are present.

Mixing in powders generally results from relative motion of groups of particles – convective mixing – or of individuals – diffusive mixing. Segregation or demixing occurs when the motion of individual particles is biased according to their particular characteristics – size, shape, composition etc. In the absence of such bias, individual motion invariably leads to homogenization of the mixture. Relationships between mixing/segregation processes and the external and interparticle forces responsible for causing or opposing relative motion are reviewed. Specific examples of mixing and segregation in flow over surfaces, in rotating cylinders and other applications are described.

We consider simultaneous blind deconvolution of $r$ source signals from their noisy superposition, a problem also referred to blind demixing and deconvolution. This signal processing problem occurs in the context of the Internet of Things where a massive number of sensors sporadically communicate only short messages over unknown channels. We show that robust recovery of message and channel vectors can be achieved via convex optimization when random linear encoding using i.i.d. complex Gaussian matrices is used at the devices and the number of required measurements at the receiver scales with the degrees of freedom of the overall estimation problem. Since the scaling is linear in $r$ our result significantly improves over recent works. [ABSTRACT FROM AUTHOR]

We study the problem of demixing a pair of sparse signals from noisy, nonlinear observations of their superposition. Mathematically, we consider a nonlinear signal observation model, y_i = g(a_i^Tx) + e_i, \ i=1,\ldots,m, where x = \Phi w+\Psi z denotes the superposition signal, \Phi and \Psi, and w, z\in \mathbb {R}^n are sparse coefficient vectors of the constituent signals, and e_i represents the noise. Moreover, g represents a nonlinear link function, and a_i\in \mathbb {R}^n is the ith row of the measurement matrix A\in \mathbb R^m\times n. Problems of this nature arise in several applications ranging from astronomy, computer vision, and machine learning. In this paper, we make some concrete algorithmic progress for the above demixing problem. Specifically, we consider two scenarios: first, the case when the demixing procedure has no knowledge of the link function, and second is the case when the demixing algorithm has perfect knowledge of the link function. In both cases, we provide fast algorithms for recovery of the constituents w and $z$ from the observations. Moreover, we support these algorithms with a rigorous theoretical analysis and derive (nearly) tight upper bounds on the sample complexity of the proposed algorithms for achieving stable recovery of the component signals. We also provide a range of numerical simulations to illustrate the performance of the proposed algorithms on both real and synthetic signals and images. [ABSTRACT FROM PUBLISHER]

Suppose that we have r sensors and each one intends to send a function {g}_{i} (e.g., a signal or an image) to a receiver common to all r sensors. During transmission, each gi gets convolved with a function {f}i . The receiver records the function y , given by the sum of all these convolved signals. When and under which conditions is it possible to recover the individual signals gi and the blurring functions fi from just one received signal y ? This challenging problem, which intertwines blind deconvolution with blind demixing, appears in a variety of applications, such as audio processing, image processing, neuroscience, spectroscopy, and astronomy. It is also expected to play a central role in connection with the future Internet-of-Things. We will prove that under reasonable and practical assumptions, it is possible to solve this, otherwise, highly ill-posed problem and recover the $r$ transmitted functions gi and the impulse responses fi in a robust, reliable, and efficient manner, from just one single received function y by solving a semidefinite program. We derive explicit bounds on the number of measurements needed for successful recovery and prove that our method is robust in the presence of noise. Our theory is actually suboptimal, since numerical experiments demonstrate that, quite remarkably, recovery is still possible if the number of measurements is close to the number of degrees of freedom. [ABSTRACT FROM PUBLISHER]

Two approximations recovering the functions from their transformed moments are proposed. The upper bounds for the uniform rate of convergence are derived. In addition, the comparisons of the estimates of the cumulative distribution function and its density function with the empirical distribution and the kernel density estimates are conducted via a simulation study. The plots of recovered functions are presented for several examples as well. [ABSTRACT FROM PUBLISHER]

A number of calcium imaging methods have been developed to monitor the activity of large populations of neurons. One particularly promising approach, Bessel imaging, captures neural activity from a volume by projecting within the imaged volume onto a single imaging plane, therefore effectively mixing signals and increasing the number of neurons imaged per pixel. These signals must then be computationally demixed to recover the desired neural activity. Unfortunately, currently-available demixing methods can perform poorly in the regime of high imaging density (i.e., many neurons per pixel). In this work we introduce a new pipeline (maskNMF) for demixing dense calcium imaging data. The main idea is to first denoise and temporally sparsen the observed video; this enhances signal strength and reduces spatial overlap significantly. Next we detect neurons in the sparsened video using a neural network trained on a library of neural shapes. These shapes are derived from segmented electron microscopy images input into a Bessel imaging model; therefore no manual selection of "good" neural shapes from the functional data is required here. After cells are detected, we use a constrained non-negative matrix factorization approach to demix the activity, using the detected cells' shapes to initialize the factorization. We test the resulting pipeline on both simulated and real datasets and find that it is able to achieve accurate demixing on denser data than was previously feasible, therefore enabling faithful imaging of larger neural populations. The method also provides good results on more "standard" two-photon imaging data. Finally, because much of the pipeline operates on a significantly compressed version of the raw data and is highly parallelizable, the algorithm is fast, processing large datasets faster than real time.

With the objective of clarifying the phenomena taking place during the synthesis of high impact polystyrene (HIPS), polymeric mixtures between polystyrene (PS) or polybutadiene (PB) and a star-shaped poly(styrene-butadiene) copolymer (BC) were prepared using ethylbenzene (EB) as a solvent. The molar mass of PS, the BC concentration and the total mass fraction of the PS were varied. The morphology of some of the mixtures or isolated phases was observed by transmission electron microscopy. It was found that the stability of the homopolymer/BC/EB blends increased when their viscosity and affinity between its components were higher. Both, the affinity and the distribution of the components when demixing occurred, were dependent upon the concentration of BC and the relationship between the molar masses of the blocks in BC and each one of the homopolymers investigated. The mixtures PS/BC were stable, except for the case with the high PS molar mass and the highest BC concentration. In this case and also for the PS - rich isolated phase, BC exhibited lamellar microdomains dispersed in a continuous PS-rich phase. The number and diameter of these microdomains were dependent upon the BC concentration in the PS matrix.

Dynamic density functional theory calculations of fluid–fluid demixing on spherical geometries are characterized via their angular power spectrum as well as via the Minkowski functionals (MFs) of their binarized fluid density fields. MFs form a complete set of additive, motion invariant and continuous morphological measures sensitive to nonlinear (spatial) correlations. The temporal evolution of the fluid density fields is analyzed for different sphere sizes and mixing compositions. The demixing process in the stages of early spinodal decomposition and consecutive domain growth can be characterized by both methods and a power-law domain growth $L(t)\propto {t}^{\alpha }$ is evidenced for the MF measures. The average domain size obtained by the structure factor only responds to the late stage domain growth of the demixing process. MFs provide refined insights into the demixing process: they allow the detection of distinct stages in the early spinodal decomposition, provide a precise measure of the relative species composition of the mixture and, most importantly: after a proper rescaling, they allow the detection of a universal demixing behavior for a wide range of mixture fractions and for different sphere sizes.

Neutron diffraction in combination with isotopic substitution on the zero-scatterer 62 Ni 43 63 Cu 57 shows indications for chemical short-range order in the stable liquid as evidenced by oscillations in the concentration-concentration structure factor S CC ( q ). This points towards a non-ideal solution behavior of Ni-Cu contrary to common believe but in agreement with measurements of free enthalpy of mixing. The temperature dependence of S CC at small momentum transfer provides evidence of critical compositional fluctuations in Ni 43 Cu 57 melts., (Creative Commons Attribution license.)

The manuscript focuses on the demixing of hyaluronan and alginate in the hydrogel state. Binary solutions of the two polysaccharides have been treated with Ca 2+ as the alginate cross-linking ion and the radial distribution of the two components in the hydrogels was measured by means of 1 H NMR. These results revealed the presence of alginate-enriched and hyaluronan-enriched domains stemming from a polysaccharide demixing. The hydrogels were characterized by means of uniaxial compression and creep-compliance measurements which showed that the demixing increased the overall resistance of the hydrogel to stress. In addition, due to the viscoelastic properties of hyaluronan, a marked increase of the Newtonian viscosity of the constructs was noticed. The peculiarity of the effect of hyaluronan was demonstrated by the use of an alginate unable to form gel by binding non-calcium binding alginate, i.e. mannuronan, ruling out the effect of viscosity over the time-dependent behavior of the mixed hyaluronan-alginate hydrogels. [ABSTRACT FROM AUTHOR]

The volume occupied by unconstrained bacterial DNA in physiological saline solutions exceeds 1000 times the volume of the cell. Still, it is confined to a well defined region of the cell called the nucleoid, which occupies only a fraction of the cell volume. This is puzzling, because bacterial DNA is not delimited by a membrane, in sharp contrast with the nucleus of eukaryotic cells. There is still no general agreement on the mechanism leading to the compaction of the DNA and the formation of the nucleoid. However, advances in in vivo sub-wavelength resolution microscopy techniques have recently allowed the observation of the nucleoid at an unprecedented level of detail. In particular, these observations show that the compaction of the nucleoid is not static but is instead a highly dynamic feature, which depends on several factors, like the richness of the nutrient, the cell cycle stage, temperature, and the action of an osmotic shock or antibiotics. After a short description of the electrolyte content of the cytosol and a brief overview of the different mechanisms that may lead to the formation of the nucleoid, this paper reviews some of the most fascinating recent results of in vivo sub-wavelength resolution microscopy. It is furthermore argued that these observations provide converging indications in favor of a model that describes the cytosol as an aqueous electrolyte solution containing several macromolecular species, where demixing and segregative phase separation occur between DNA and RNA (essentially rRNA and mRNA involved in translation complexes, but also the large amounts of rRNA synthesized at the rrn operons of cells growing in rich media). It is also pointed out that crowding may play a crucial role through its synergy with electrostatic forces. By constraining macromolecules to remain at short distances from one another and feel electrostatic interactions in spite of the strong screening exerted by electrolyte species, crowding favors stronger DNA/RNA demixing and nucleoid compaction. [ABSTRACT FROM AUTHOR]

Using both theory and continuum simulation, we examine a system comprising a mixture of polymer chains formed from 100 hard-sphere (HS) segments and HS colloids with a diameter which is 20 times that of the polymer segments. According to Wertheim's first-order thermodynamic perturbation theory (TPT1) this athermal system is expected to phase separate into a colloid-rich and a polymer-rich phase. Using a previously developed continuous pseudo-HS potential [J. F. Jover, A. J. Haslam, A. Galindo, G. Jackson, and E. A. Muller, J. Chem. Phys.137, 144505 (2012)], we simulate the system at a phase point indicated by the theory to be well within the two-phase binodal region. Molecular-dynamics simulations are performed from starting configurations corresponding to completely phase-separated and completely pre-mixed colloids and polymers. Clear evidence is seen of the stabilisation of two coexisting fluid phases in both cases. An analysis of the interfacial tension of the phase-separated regions is made; ultra-low tensions are observed in line with previous values determined with square-gradient theory and experiment for colloid–polymer systems. Further simulations are carried out to examine the nature of these coexisting phases, taking as input the densities and compositions calculated using TPT1 (and corresponding to the peaks in the probability distribution of the density profiles obtained in the simulations). The polymer chains are seen to be fully penetrable by other polymers. By contrast, from the point of view of the colloids, the polymers behave (on average) as almost-impenetrable spheres. It is demonstrated that, while the average interaction between the polymer molecules in the polymer-rich phase is (as expected) soft-repulsive in nature, the corresponding interaction in the colloid-rich phase is of an entirely different form, characterised by a region of effective intermolecular attraction. [ABSTRACT FROM PUBLISHER]

We study the interface evolution of a series of periodic Co/Mo 2 C multilayers as a function of the annealing temperature up to 600 °C. Different complementary techniques are implemented to get information on the phenomenon taking place at the interfaces of the stack. The periodical structure of Co/Mo 2 C multilayer is proven by time-of-flight secondary ion mass spectrometry (ToF-SIMS) depth profiles which demonstrate the formation of an oxide layer at both air/stack and stack/substrate interfaces. From Nuclear magnetic resonance (NMR) spectra, we observed the intermixing phenomenon of Co and C atoms for the as-deposited sample, and then at annealing temperature above 300 °C Co and C atoms separate from their mixed regions. Comparison of NMR results between Co/Mo 2 C and Co/C references confirms this phenomenon. This is in agreement with X-ray emission spectroscopy (XES) measurements. Furthermore the calculation of the Co–C, Co–Mo and Mo–C mixing enthalpy using Miedema's model gives a proof of the demixing of Co and C atoms present within the stacks above 300 °C. From the transmission electron microscopy (TEM) analysis, we found the presence of some crystallites within the as-deposited sample as well as the mainly amorphous nature of all layers. This is confirmed using X-ray diffraction (XRD) patterns which also demonstrate the growth of crystallites induced upon annealing. [ABSTRACT FROM AUTHOR]

The weak intermacromolecular interactions caused by the presence of a complexing agent in two phase biopolymer mixture can affect its phase equilibrium and morphology. In this communication, the attempt was performed to induce demixing in semidilute and highly compatible sodium caseinate/sodium alginate system (SC-SA) mixtures in the presence of sodium salt of dextran sulfate (DSS) at pH 7.0, (above the isoelectrical point of caseins), and to characterize phase equilibrium, intermacromolecular interactions, and structure of such systems by rheo-small angle light scattering (SALS), optical microscopy (OM), phase analysis, dynamic light scattering (DLS), fast protein liquid chromatography (FPLC), ESEM, and rheology. Addition of dextran sulfate sodium salt (DSS) to the semidilute single phase SC-SA system, even in trace concentrations (10-3 wt %), leads to segregative liquid-liquid phase separation, and a substantial increase in storage and loss moduli of the system. The degree of the protein conversion in the complex grows, when the concentration of SC in the system increases from 1 to 2 wt %. It is also established here that demixing of semidilute biopolymer mixtures, induced by the minor presence of DSS is a rather common phenomenon, because its also was observed here for other biopolymer pairs. At high shear rates SC becomes even less compatible with SA in the presence of DSS than at rest. Experimental observations suggest that the approach for inducing demixing of semidilute and highly compatible biopolymer mixtures by physical interactions of the constituents is a promising tool for regulation of biopolymer compatibility and achieving better predictions of phase behavior of aqueous proteincharged polysaccharide systems. [ABSTRACT FROM AUTHOR]