Designing spin-textured flat bands in twisted graphene multilayers via helimagnet encapsulation

Twisted graphene multilayers provide tunable platforms to engineer flat bands and exploit the associated strongly correlated physics. The two-dimensional nature of these systems makes them suitable for encapsulation by materials that break specific symmetries. In this context, recently discovered two-dimensional helimagnets, such as the multiferroic monolayer NiI2, are specially appealing for breaking time-reversal and inversion symmetries due to their nontrivial spin textures. Here we show that this spin texture can be imprinted on the electronic structure of twisted bilayer graphene by proximity effect. We discuss the dependence of the imprinted spin texture on the wave-vector of the helical structure, and on the strength of the effective local exchange field. Based on these results we discuss the nature of the superconducting instabilities that can take place in helimagnet encapsulated twisted bilayer graphene. Our results put forward helimagnetic encapsulation as a powerful way of designing spin-textured flat band systems, providing a starting point to engineer a new family of correlated moire states.

A Mathematical Model for Transport in Poroelastic Materials with Variable Volume: Derivation, Lie Symmetry Analysis and Examples. Part 2

The model for perfused tissue undergoing deformation taking into account the local exchange between tissue and blood and lymphatic systems is presented. The Lie symmetry analysis in order to identify its symmetry properties is applied. Several families of steady-state solutions in closed formulae are derived. An analysis of the impact of the parameter values and boundary conditions on the distribution of hydrostatic pressure, osmotic agent concentration and deformation of perfused tissue is provided applying the solutions obtained in examples describing real-world processes.

The case against alternative currencies

Local Currencies, Local Exchange Trading Systems, and Time Banks are all part of a new social movement that aims to restrict money's purchasing power within a certain geographic area, or within a certain community. According to their proponents, these restrictions may contribute to building sustainable local economies, supporting local businesses and creating “warmer” social relations. This article inquires whether the overall enthusiasm that surrounds alternative currencies is justified. It argues that the potential benefits of these currencies are not sufficient to justify the restrictions they impose on money's purchasing power. Turning these currencies into effective channels of change, by increasing their scope and their strength, could severely hinder the pursuit of social justice, in a way that is probably not even necessary for achieving their objectives. The paper concludes that large-scale limitations of money's purchasing power are, therefore, undesirable.

Development of the Method for Predicting and Calculating the Operation of Sorption Systems for Cleaning the Generator Gas based on Dolomite Use. Part II

At present, instead of a direct combustion of solid fuel, its thermochemical conversion is exten-sively used to produce a generator gas. The use of this technology is connected with the need for gas purification. One of the promising and widely spread sorbents for the purification of the generator gas is dolomite, whose particles compose the active component of the bed filters. Forecasting the technological characteristics of the functioning of the bed filters of a various de-sign is an extremely urgent task. The objective of the study is to develop a method for forecast-ing and calculating the operation of sorption systems for purification of the generator gas based on dolomite. It is achieved by constructing and verifying a mathematical model of the function-ing of the bed sorption filter with a radial-axial flow pattern of the generator gas through the do-lomite filling. The Markov chains theory of a mathematical apparatus is used to design the one-dimensional mathematical model of the process with discrete space and time. The main recurrent balance ratio is formed at each calculation step taking into account the current characteristics of the process, which makes the model nonlinear. The significance of the research is that an approach to the problem of increasing the reliability of the description and reliability of forecasting technological processes in a bed filter was proposed based on the construction of mathematical models of these processes, in which the filter is considered as a system with distributed characteristics, and the calculation was based on local exchange potentials between particles and gas.

Low-Order Scaling Quasiparticle Self-Consistent GW for Molecules

Low-order scaling GW implementations for molecules are usually restricted to approximations with diagonal self-energy. Here, we present an all-electron implementation of quasiparticle self-consistent GW for molecular systems. We use an efficient algorithm for the evaluation of the self-energy in imaginary time, from which a static non-local exchange-correlation potential is calculated via analytical continuation. By using a direct inversion of iterative subspace method, fast and stable convergence is achieved for almost all molecules in the GW100 database. Exceptions are systems which are associated with a breakdown of the single quasiparticle picture in the valence region. The implementation is proven to be starting point independent and good agreement of QP energies with other codes is observed. We demonstrate the computational efficiency of the new implementation by calculating the quasiparticle spectrum of a DNA oligomer with 1,220 electrons using a basis of 6,300 atomic orbitals in less than 4 days on a single compute node with 16 cores. We use then our implementation to study the dependence of quasiparticle energies of DNA oligomers consisting of adenine-thymine pairs on the oligomer size. The first ionization potential in vacuum decreases by nearly 1 electron volt and the electron affinity increases by 0.4 eV going from the smallest to the largest considered oligomer. This shows that the DNA environment stabilizes the hole/electron resulting from photoexcitation/photoattachment. Upon inclusion of the aqueous environment via a polarizable continuum model, the differences between the ionization potentials reduce to 130 meV, demonstrating that the solvent effectively compensates for the stabilizing effect of the DNA environment. The electron affinities of the different oligomers are almost identical in the aqueous environment.

Machine learning the derivative discontinuity of density-functional theory

Machine learning is a powerful tool to design accurate, highly non-local, exchange-correlation functionals for density functional theory. So far, most of those machine learned functionals are trained for systems with an integer number of particles. As such, they are unable to reproduce some crucial and fundamental aspects, such as the explicit dependency of the functionals on the particle number or the infamous derivative discontinuity at integer particle numbers. Here we propose a solution to these problems by training a neural network as the universal functional of density-functional theory that (i) depends explicitly on the number of particles with a piece-wise linearity between the integer numbers and (ii) reproduces the derivative discontinuity of the exchange-correlation energy. This is achieved by using an ensemble formalism, a training set containing fractional densities, and an explicitly discontinuous formulation.

Splay states and two-cluster states in ensembles of excitable units

Focusing on systems of sinusoidally coupled active rotators, we study the emergence and stability of periodic collective oscillations for systems of identical excitable units with repulsive all-to-all interaction. Special attention is put on splay states and two-cluster states. Recently, it has been shown that one-parameter families of such systems, containing the parameter values at which the Watanabe–Strogatz integrability takes place, feature an instantaneous non-local exchange of stability between splay and two-cluster states. Here, we illustrate how in the extended families that circumvent the Watanabe–Strogatz dynamics, this abrupt transition is replaced by the “gradual transfer” of stability between the 2-cluster and the splay states, mediated by mixed-type solutions. We conclude our work by recovering the same kind of dynamics and transfer of stability in an ensemble of voltage-coupled Morris–Lecar neurons.

Theoretical Band and Confinement Interpretation of 1D Electrons: Impact on Plasmons and Exchange-Correlation Functionals

Theoretical band and confinement interpretation of electron gas in lowest energy sub-band of quasi- 1D metallic wire have been done. Counter effects have been investigated on electrostatic oscillations (plasmons) determined by the electron density response function. Carrier correlations are treated by incorporating the local exchange-correlation (XC) effects within mean- field approximation. Results obtained are in quantitative agreement with experiments data of Nagao et al. (2006 Phys. Rev. Lett. 97 116802). Variation in both degeneracy and confinement potential cause a clear energy- shift in the electrostatic oscillations accomplished by asymmetry in band effective mass. Resultant massasymmetry is attributed to the greater strength of XC- effects. These contributions turns out to be quite logical in describing the splitting of 1D-bands over ad-hoc spin-orbital splitting idea of Nagao et al. Calculated XC-functionals agreed well with the lattice regularized diffusion Monte Carlo (LRDMC) simulation data (2006 Phys. Rev. B 74, 245427, 2009 J. Phys. A:Math.Theor.42 214021). Competition among XC-functionals and kinetic energy tendencies decides a criterion by satisfying which a metallic quasi-1D wire may undergo an instability at certain critical temperature (Tc).

A co-culture microplate for real-time measurement of microbial interactions

The dynamic structures of microbial communities emerge from the complex network of interactions between their constituent microbial organisms. Quantitative measurements of these microbial interactions are important for understanding and engineering microbial community structure. Here, we present the development and application of the BioMe plate, a redesigned microplate device in which pairs of wells are separated by porous membranes. BioMe facilitates the measurement of dynamic microbial interactions and integrates easily with standard laboratory equipment. We first applied BioMe to recapitulate recently characterized, natural symbiotic interactions between bacteria isolated from the D. melanogaster gut microbiome. Specifically, the BioMe plate allowed us to observe the benefit provided by two Lactobacilli strains to an Acetobacter strain. We next explored the use of BioMe to gain quantitative insight into the engineered obligate syntrophic interaction between a pair of E. coli amino acid auxotrophs. We integrated experimental observations with a mechanistic computational model to quantify key parameters associated with this syntrophic interaction, including metabolite secretion and diffusion rates. This model also allowed us to explain the slow growth observed for auxotrophs growing in adjacent wells, by demonstrating that under the relevant range of parameters, local exchange between auxotrophs is essential for efficient growth. The BioMe plate provides a scalable and flexible approach for the study of dynamic microbial interactions.