Engineering Plateau Phase Transition in Quantum Anomalous Hall Multilayers.

The plateau phase transition in quantum anomalous Hall (QAH) insulators corresponds to a quantum state wherein a single magnetic domain gives way to multiple domains and then reconverges back to a single magnetic domain. The layer structure of the sample provides an external knob for adjusting the Chern number C of the QAH insulators. Here, we employ molecular beam epitaxy to grow magnetic topological insulator multilayers and realize the magnetic field-driven plateau phase transition between two QAH states with odd Chern number change ΔC. We find that critical exponents extracted for the plateau phase transitions with ΔC = 1 and ΔC = 3 in QAH insulators are nearly identical. We construct a four-layer Chalker-Coddington network model to understand the consistent critical exponents for the plateau phase transitions with ΔC = 1 and ΔC = 3. This work will motivate further investigations into the critical behaviors of plateau phase transitions with different ΔC in QAH insulators.

Performance reserves in brain-imaging-based phenotype prediction.

This study examines the impact of sample size on predicting cognitive and mental health phenotypes from brain imaging via machine learning. Our analysis shows a 3- to 9-fold improvement in prediction performance when sample size increases from 1,000 to 1 M participants. However, despite this increase, the data suggest that prediction accuracy remains worryingly low and far from fully exploiting the predictive potential of brain imaging data. Additionally, we find that integrating multiple imaging modalities boosts prediction accuracy, often equivalent to doubling the sample size. Interestingly, the most informative imaging modality often varied with increasing sample size, emphasizing the need to consider multiple modalities. Despite significant performance reserves for phenotype prediction, achieving substantial improvements may necessitate prohibitively large sample sizes, thus casting doubt on the practical or clinical utility of machine learning in some areas of neuroimaging.

Global quantum discord in the Lipkin-Meshkov-Glick model at zero and finite temperatures.

We study the global quantum discord (GQD) in the Lipkin-Meshkov-Glick (LMG) model at zero and finite temperatures, in which all spins are mutually interacted and introduced in an external magnetic field (denoted byh). We confirm that the high coordinate number is one of the most distinguishing features of the LMG model, which directly results in the nontrivial behaviors of quantum correlations. We compare the GQD with other quantum correlations measures (such as concurrence, quantum discord, and global entanglement) and find the remarkable difference between them. For instance, we find that GQD spreads in the entire system and captures more information on quantum correlations when comparing with concurrence and quantum (pairwise) discord. We discover that GQD can characterize multipartite correlations in the both broken phase (h< 1) and the symmetric phase (h⩾ 1), while global entanglement and its generalized fail. Moreover, we show that the ground-state GQD can identify second-order quantum phase transitions of the LMG model in the thermodynamic limit. By making the scaling behavior of the GQD in the LMG model analysis, we show that GQD (denoted byG) scales asG∼k⋅N+cwithk> 0 in the anisotropic cases for any fixed magnetic field. We further show that GQD behaves asG|sn∼k⋅1N+cwithk< 0 in the isotropic cases for any Dicke state |sn⟩. Hereinkandcare the fitting parameters. We also find that the thermal stability of the GQD at low temperatures depends on the energy gap. We further reveal that the extraordinary behaviors of the thermal-state GQD in the isotropic LMG model are explained by the contribution theory of the energy levels.

Scaling Behavior of Ionic Transport in Membrane Nanochannels.

Ionic conductance in membrane channels exhibits a power-law dependence on electrolyte concentration ( G ∼ cα). The many scaling exponents, α, reported in the literature usually require detailed interpretations concerning each particular system under study. Here, we critically evaluate the predictive power of scaling exponents by analyzing conductance measurements in four biological channels with contrasting architectures. We show that scaling behavior depends on several interconnected effects whose contributions change with concentration so that the use of oversimplified models missing critical factors could be misleading. In fact, the presence of interfacial effects could give rise to an apparent universal scaling that hides the channel distinctive features. We complement our study with 3D structure-based Poisson-Nernst-Planck (PNP) calculations, giving results in line with experiments and validating scaling arguments. Our findings not only provide a unified framework for the study of ion transport in confined geometries but also highlight that scaling arguments are powerful and simple tools with which to offer a comprehensive perspective of complex systems, especially those in which the actual structure is unknown.

Fundamentals and characterizations of scratch resistance on automotive clearcoats.

As original equipment manufacturers (OEMs) strive to deliver improved coating performance with a sustainable footprint, opportunities for innovation are emerging, particularly on improving mechanical properties, appearance, and solids content. Resistance to scratch and mar damage is one of the key performance attributes that has been emphasized by both OEMs and consumers to maintain a vehicle's appearance and corrosion resistance over its service lifetime. Fundamental methodologies including instrumented scratch measurements at multiple size scales are used in this work as part of a product development strategy to better understand the scratch and mar behavior of automotive topcoats. This study compares physical properties of several melamin-formaldehyde and isocyanate cured clearcoats over the appropriate basecoats. Micro- and nano-scratch techniques were employed in combination with industry standard method, Amtec-Kistler carwash to identify performance differences under different scratch conditions. Mechanical and viscoelastic properties of the coatings were studied using tensile tests and dynamic mechanical thermal analysis (DMTA) to better understand the failure mechanisms associated with plastic deformation and fracture at different scratch scales. The information gathered from the above testing protocols is used to analyze coating performance in terms of the contact strain, transitions between elastic - plastic behavior, coefficient of friction and stress localization.

Effects of Orthostatism and Hemodialysis on Mean Heart Period and Fractal Heart Rate Properties of Chronic Renal Failure Patients.

The aim of this work was to evaluate the short-term fractal index (α1 ) of heart rate variability (HRV) in chronic renal failure (CRF) patients by identifying the effects of orthostatism and hemodialysis (HD), and by evaluating the correlation between α1 and the mean RR interval from sinus beats (meanNN). HRV time series were derived from ECG data of 19 CRF patients and 20 age-matched healthy subjects obtained at supine and orthostatic positions (lasting 5 min each). Data from CRF patients were collected before and after HD. α1 was calculated from each time series and compared by analysis of variance. Pearson's correlations between meanNN and α1 were calculated using the data from both positions by considering three groups: healthy subjects, CRF before HD and CRF after HD. At supine position, α1 of CRF patients after HD (1.17 ± 0.30) was larger (P < 0.05) than in healthy subjects (0.89 ± 0.28) but not before HD (1.10 ± 0.34). α1 increased (P < 0.05) in response to orthostatism in healthy subjects (1.29 ± 0.26) and CRF patients after HD (1.34 ± 0.31), but not before HD (1.25 ± 0.37). Whereas α1 was correlated (P < 0.05) with the meanNN of healthy subjects (r = -0.562) and CRF patients after HD (r = -0.388), no significance in CRF patients before HD was identified (r = 0.003). Multiple regression analysis confirmed that α1 was mainly predicted by the orthostatic position (in all groups) and meanNN (healthy subjects and patients after HD), showing no association with the renal disease condition in itself. In conclusion, as in healthy subjects, α1 of CRF patients correlates with meanNN after HD (indicating a more irregular-like HRV behavior at slower heart rates). This suggests that CRF patients with stable blood pressure preserve a regulatory adaptability despite a shifted setting point of the heart period (i.e., higher heart rate) in comparison with healthy subjects.

Self-Organizing Arrays of Size Scalable Nanoparticle Rings.

A central challenge in nano- and mesoscale materials research is facile formation of specific structures for catalysis, sensing, and photonics. Self-assembled equilibrium structures, such as three-dimensional crystals or ordered monolayers, form as a result of the interactions of the constituents. Other structures can be achieved by imposing forces (fields) and/or boundary conditions, which Whitesides termed "self-organization". Here, we demonstrate contact line pinning on locally curved surfaces (i.e., a self-assembled monolayer of SiO2 colloidal particles) as a boundary condition to create extended arrays of uniform rings of Au nanoparticles (NPs) on the SiO2 colloids. The mechanism differs from the well-known "coffee-ring" effect; here the functionalized NPs deposit at the contact line and are not driven by evaporative transport. Thus, NP ring formation depends on the hydrophobicity and wetting of the SiO2 colloids by the chloroform solution, ligands on the NPs, and temperature. The NP rings exhibit size scaling behavior, maintaining a constant ratio of NP ring-to-colloid diameter (from 300 nm to 2 µm). The resultant high-quality NP ring structures are expected to have interesting photonic properties.

Polyelectrolyte Threading through a Nanopore.

Threading charged polymers through a nanopore, driven by electric fields E, is investigated by means of Langevin dynamics simulations. The mean translocation time 〈 τ 〉 is shown to follow a scaling law Nα, and the exponent α increases monotonically from 1.16 (4) to 1.40 (3) with E. The result is double-checked by the calculation of mean square displacement of translocation coordinate, which asserts a scaling behavior tß (for t near τ) with ß complying with the relation αß = 2. At a fixed chain length N, 〈τ〉 displayed a reciprocal scaling behavior E-1 in the weak and also in the strong fields, connected by a transition E-1.64(5) in the intermediate fields. The variations of the radius of gyration of chain and the positions of chain end are monitored during a translocation process; far-from-equilibrium behaviors are observed when the driving field is strong. A strong field can strip off the condensed ions on the chain when it passes the pore. The total charges of condensed ions are hence decreased. The studies for the probability and density distributions reveal that the monomers in the trans-region are gathered near the wall and form a pancake-like density profile with a hump cloud over it in the strong fields, due to fast translocation.

Metabolic imaging in multiple time scales.

We report here a novel combination of time-resolved imaging methods for probing mitochondrial metabolism in multiple time scales at the level of single cells. By exploiting a mitochondrial membrane potential reporter fluorescence we demonstrate the single cell metabolic dynamics in time scales ranging from microseconds to seconds to minutes in response to glucose metabolism and mitochondrial perturbations in real time. Our results show that in comparison with normal human mammary epithelial cells, the breast cancer cells display significant alterations in metabolic responses at all measured time scales by single cell kinetics, fluorescence recovery after photobleaching and by scaling analysis of time-series data obtained from mitochondrial fluorescence fluctuations. Furthermore scaling analysis of time-series data in living cells with distinct mitochondrial dysfunction also revealed significant metabolic differences thereby suggesting the broader applicability (e.g. in mitochondrial myopathies and other metabolic disorders) of the proposed strategies beyond the scope of cancer metabolism. We discuss the scope of these findings in the context of developing portable, real-time metabolic measurement systems that can find applications in preclinical and clinical diagnostics.

Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signals.

We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences.

Atomic Force Microscopy Study of the Kinetic Roughening in Nanostructured Gold Films on SiO2.

Dynamic scaling behavior has been observed during the room-temperature growth of sputtered Au films on SiO2using the atomic force microscopy technique. By the analyses of the dependence of the roughness, σ, of the surface roughness power,P(f), and of the correlation length,ξ, on the film thickness,h, the roughness exponent,α = 0.9 ± 0.1, the growth exponent,ß = 0.3 ± 0.1, and the dynamic scaling exponent,z = 3.0 ± 0.1 were independently obtained. These values suggest that the sputtering deposition of Au on SiO2at room temperature belongs to a conservative growth process in which the Au grain boundary diffusion plays a dominant role.