Sandwich-like Catalyst–Carbon–Catalyst Trilayer Structure as a Compact 2D Host for Highly Stable Lithium–Sulfur Batteries

Herein, we propose the construction of a sandwich-structured host filled with continuous 2D catalysis–conduction interfaces. This MoN-C-MoN trilayer architecture causes the strong conformal adsorption of S/Li₂S_x and its high-efficiency conversion on the two-sided nitride polar surfaces, which are supplied with high-flux electron transfer from the buried carbon interlayer. The 3D self-assembly of these 2D sandwich structures further reinforces the interconnection of conductive and catalytic networks. The maximized exposure of adsorptive/catalytic planes endows the MoN-C@S electrode with excellent cycling stability and high rate performance even under high S loading and low host surface area. The high conductivity of this trilayer texture does not compromise the capacity retention after the S content is increased. Such a job-synergistic mode between catalytic and conductive functions guarantees the homogeneous deposition of S/Li₂S_x, and avoids thick and devitalized accumulation (electrode passivation) even after high-rate and long-term cycling.     

Direct Intermediate Regulation Enabled by Sulfur Containers in Working Lithium–Sulfur Batteries

Polysulfide intermediates (PSs), the liquid-phase species of active materials in lithium–sulfur (Li-S) batteries, connect the electrochemical reactions between insulative solid sulfur and lithium sulfide and are key to full exertion of the high-energy-density Li-S system. Herein, the concept of sulfur container additives is proposed for the direct modification on the PSs species. By reversible storage and release of the sulfur species, the container molecule converts small PSs into large organosulfur species. The prototype di(tri)sulfide-polyethylene glycol sulfur container is highly efficient in the reversible PS transformation to multiply affect electrochemical behaviors of sulfur cathodes in terms of liquid-species clustering, reaction kinetics, and solid deposition. The stability and capacity of Li-S cells was thereby enhanced. The sulfur container is a strategy to directly modify PSs, enlightening the precise regulation on Li-S batteries and multi-phase electrochemical systems.     

Maximum of the Characteristic Polynomial for a Random Permutation Matrix

Let P_N be a uniform random N × N permutation matrix and let χ_N(z) = det(zI_N − P_N) denote its characteristic polynomial. We prove a law of large numbers for the maximum modulus of χ_N on the unit circle, specifically, with probability tending to 1 as N → ∞ , for a numerical constant x₀ ≈ 0.652 . The main idea of the proof is to uncover a logarithmic correlation structure for the distribution of (the logarithm of) χ_N , viewed as a random field on the circle, and to adapt a well-known second-moment argument for the maximum of the branching random walk. Unlike the well-studied CUE field in which P_N is replaced with a Haar unitary, the distribution of χ_N(e^2πit) is sensitive to Diophantine properties of the point t . To deal with this we borrow tools from the Hardy-Littlewood circle method. © 2020 Wiley Periodicals LLC     

The quartet theory of human emotions: An integrative and neurofunctional model

Despite an explosion of research in the affective sciences during the last few decades, interdisciplinary theories of human emotions are lacking. Here we present a neurobiological theory of emotions that includes emotions which are uniquely human (such as complex moral emotions), considers the role of language for emotions, advances the understanding of neural correlates of attachment-related emotions, and integrates emotion theories from different disciplines. We propose that four classes of emotions originate from four neuroanatomically distinct cerebral systems. These emotional core systems constitute a quartet of affect systems: the brainstem-, diencephalon-, hippocampus-, and orbitofrontal-centred affect systems. The affect systems were increasingly differentiated during the course of evolution, and each of these systems generates a specific class of affects (e.g., ascending activation, pain/pleasure, attachment-related affects, and moral affects). The affect systems interact with each other, and activity of the affect systems has effects on – and interacts with – biological systems denoted here as emotional effector systems. These effector systems include motor systems (which produce actions, action tendencies, and motoric expression of emotion), peripheral physiological arousal, as well as attentional and memory systems. Activity of affect systems and effector systems is synthesized into an emotion percept (pre-verbal subjective feeling), which can be transformed (or reconfigured) into a symbolic code such as language. Moreover, conscious cognitive appraisal (involving rational thought, logic, and usually language) can regulate, modulate, and partly initiate, activity of affect systems and effector systems. Our emotion theory integrates psychological, neurobiological, sociological, anthropological, and psycholinguistic perspectives on emotions in an interdisciplinary manner, aiming to advance the understanding of human emotions and their neural correlates.     

The Landscape of the Spiked Tensor Model

We consider the problem of estimating a large rank-one tensor u ^⊗k ∈ (ℝⁿ)^⊗k , k ≥ 3 , in Gaussian noise. Earlier work characterized a critical signal-to-noise ratio λ  _Bayes = O(1) above which an ideal estimator achieves strictly positive correlation with the unknown vector of interest. Remarkably, no polynomial-time algorithm is known that achieved this goal unless λ ≥ Cn^{(k − 2)/4} , and even powerful semidefinite programming relaxations appear to fail for 1 ≪ λ ≪ n^{(k − 2)/4} . In order to elucidate this behavior, we consider the maximum likelihood estimator, which requires maximizing a degree-k homogeneous polynomial over the unit sphere in n dimensions. We compute the expected number of critical points and local maxima of this objective function and show that it is exponential in the dimensions n , and give exact formulas for the exponential growth rate. We show that (for λ larger than a constant) critical points are either very close to the unknown vector u or are confined in a band of width Θ(λ^{−1/(k − 1)}) around the maximum circle that is orthogonal to u . For local maxima, this band shrinks to be of size Θ(λ^{−1/(k − 2)}) . These “uninformative” local maxima are likely to cause the failure of optimization algorithms. © 2019 Wiley Periodicals, Inc.     

Self-Assembly Behavior and Application of Terphenyl-Cored Trimaltosides for Membrane-Protein Studies: Impact of Detergent Hydrophobic Group Geometry on Protein Stability

Amphipathic agents are widely used in various fields including biomedical sciences. Micelle-forming detergents are particularly useful for in vitro membrane-protein characterization. As many conventional detergents are limited in their ability to stabilize membrane proteins, it is necessary to develop novel detergents to facilitate membrane-protein research. In the current study, we developed novel trimaltoside detergents with an alkyl pendant-bearing terphenyl unit as a hydrophobic group, designated terphenyl-cored maltosides (TPMs). We found that the geometry of the detergent hydrophobic group substantially impacts detergent self-assembly behavior, as well as detergent efficacy for membrane-protein stabilization. TPM-Vs, with a bent terphenyl group, were superior to the linear counterparts (TPM-Ls) at stabilizing multiple membrane proteins. The favorable protein stabilization efficacy of these bent TPMs is likely associated with a binding mode with membrane proteins distinct from conventional detergents and facial amphiphiles. When compared to n-dodecyl-β-d -maltoside (DDM), most TPMs were superior or comparable to this gold standard detergent at stabilizing membrane proteins. Notably, TPM-L3 was particularly effective at stabilizing the human β₂ adrenergic receptor (β₂AR), a G-protein coupled receptor, and its complex with G_s protein. Thus, the current study not only provides novel detergent tools that are useful for membrane-protein study, but also suggests a critical role for detergent hydrophobic group geometry in governing detergent efficacy.