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Abstract The polymorphic transition from 2H to 1 $${T}^{{\prime} }$$ T ′ -MoTe2, which was thought to be induced by high-energy photon irradiation among many other means, has been intensely studied for its technological relevance in nanoscale transistors due to the remarkable improvement in electrical performance. However, it remains controversial whether a crystalline 1 $${T}^{{\prime} }$$ T ′ phase is produced because optical signatures of this putative transition are found to be associated with the formation of tellurium clusters instead. Here we demonstrate the creation of an intrinsic 1 $${T}^{{\prime} }$$ T ′ lattice after irradiating a mono- or few-layer 2H-MoTe2 with a single field-enhanced terahertz pulse. Unlike optical pulses, the low terahertz photon energy limits possible structural damages. We further develop a single-shot terahertz-pump-second-harmonic-probe technique and reveal a transition out of the 2H-phase within 10 ns after photoexcitation. Our results not only provide important insights to resolve the long-standing debate over the light-induced polymorphic transition in MoTe2 but also highlight the unique capability of strong-field terahertz pulses in manipulating quantum materials.

We show that pressure applied to twisted WSe_{2} can enhance the many-body gap and region of stability of a fractional Chern insulator at filling ν=1/3. Our results are based on exact diagonalization of a continuum model, whose pressure dependence is obtained through ab initio methods. We interpret our results in terms of a magic line in the pressure-vs-twist angle phase diagram: along the magic line, the bandwidth of the topmost moiré valence band is minimized while simultaneously its quantum geometry resembles that of an ideal Chern band. We expect our results to generalize to other twisted transition metal dichalcogenide homobilayers.

Charge carriers in graphene can be manipulated, e.g., collimated or focused, as in conventional optics but the efficiency of these processes remains low. Zhang et al. demonstrate interference of electrons in a novel graphene microcavity device and use it to enhance collimation efficiency of the electron flow.

We present a deep neural network (DNN) -based model (HubbardNet) to variationally find the ground-state and excited-state wave functions of the one-dimensional and two-dimensional Bose-Hubbard model. Using this model for a square lattice with M sites, we obtain the energy spectrum as an analytical function of the on-site Coulomb repulsion, U, and the total number of particles, N, from a single training. This approach bypasses the need to solve a new Hamiltonian for each different set of values (U,N) and generalizes well even for out-of-distribution (U,N). Using HubbardNet, we identify the two ground-state phases of the Bose-Hubbard model (Mott insulator and superfluid). We show that the DNN-parametrized solutions are in excellent agreement with results from the exact diagonalization of the Hamiltonian, and it outperforms exact diagonalization in terms of computational scaling. These advantages suggest that our model is promising for efficient and accurate computation of exact phase diagrams of many-body lattice Hamiltonians.

Recently, topologically nontrivial polarization textures have been predicted and observed in nanoscale systems. While these polarization textures are interesting and promising in terms of applications, their topology in general is yet to be fully understood. For example, the relation between topological polarization structures and band topology has not been explored, and polar domain structures are typically considered in topologically trivial systems. In particular, the local polarization in a crystal supercell is not well-defined, and typically calculated using approximations that do not satisfy gauge invariance. Furthermore, local polarization in supercells is typically approximated using calculations involving smaller unit cells, meaning the connection to the electronic structure of the supercell is lost. In this work, we propose a definition of local polarization which is gauge invariant and can be calculated directly from a supercell without approximations. We show using first-principles calculations for commensurate bilayer hexagonal boron nitride that our expressions for local polarization give the correct result at the unit cell level, which is a first approximation to the local polarization in a moiré superlattice. We also illustrate using an effective model that the local polarization can be directly calculated in real space. Finally, we discuss the relation between polarization and band topology, for which it is essential to have a correct definition of polarization textures.

Transition metal kagome compounds have been shown to host flat bands in their bulk electronic spectrum. Here, using planar tunnelling spectroscopy supported by first-principles calculations, the authors report the signature of a novel type of flat band at the surface of antiferromagnetic kagome metal FeSn.

Abstract We utilize real-time time-dependent density functional theory and Ehrenfest dynamics scheme to investigate excited-state nonadiabatic dynamics of ligand dissociation of cobalt tricarbonyl nitrosyl, Co(CO)3NO, which is a precursor used for cobalt growth in advanced technologies, where the precursor’s reaction is enhanced by electronic excitation. Based on the first-principles calculations, we demonstrate two dissociation pathways of the NO ligand on the precursor. Detailed electronic structures are further analyzed to provide an insight into dynamics following the electronic excitations. This study sheds light on computational demonstration and underlying mechanism of the electronic-excitation-induced dissociation, especially in molecules with complex chemical bonds such as the Co(CO)3NO.

Abstract Availability of affordable and widely applicable interatomic potentials is the key needed to unlock the riches of modern materials modeling. Artificial neural network-based approaches for generating potentials are promising; however, neural network training requires large amounts of data, sampled adequately from an often unknown potential energy surface. Here we propose a self-consistent approach that is based on crystal structure prediction formalism and is guided by unsupervised data analysis, to construct an accurate, inexpensive, and transferable artificial neural network potential. Using this approach, we construct an interatomic potential for carbon and demonstrate its ability to reproduce first principles results on elastic and vibrational properties for diamond, graphite, and graphene, as well as energy ordering and structural properties of a wide range of crystalline and amorphous phases.

Here, a combined experiment-theory framework based on different nano-imaging techniques and first-principle calculations is used to analyse the shapes of moiré patterns in twisted van der Waals structures, enabling an accurate description of the coupling between the atomically thin layers.

The experimental realization of lattice-born flat bands with nontrivial topology has been elusive. Here, the authors observe topological flat bands near the Fermi level in a kagome metal CoSn, with flat bands as well as Dirac bands originating from 3d orbitals in a frustrated kagome geometry.

Direct visualization of moiré superlattices in van der Waals heterostructures is a needed diagnostic tool for the study of periodicity-induced electronic and optical phenomena. Here, the authors demonstrate that the moiré pattern in twisted bilayer graphene can be indirectly imaged by imaging the phonon polariton interference on the top hexagonal boron nitride encapsulation layer.

Using the recently proposed Susceptible–Asymptomatic–Infected–Vaccinated–Removed (SAIVR) model, we study the impact of key factors affecting COVID-19 vaccine rollout effectiveness and the susceptibility to resurgent epidemics. The SAIVR model expands the widely used Susceptible–Infectious–Removed (SIR) model for describing epidemics by adding compartments to include the asymptomatic infected (A) and the vaccinated (V) populations. We solve the model numerically to make predictions on the susceptibility to resurgent COVID-19 epidemics depending on initial vaccination coverage, importation loads, continuing vaccination, and more contagious SARS-CoV-2 variants, under persistent immunity and immunity waning conditions. The parameters of the model represent reported epidemiological characteristics of the SARS-CoV-2 virus such as the disease spread in countries with high levels of vaccination coverage. Our findings help explain how the combined effects of different vaccination coverage levels and waning immunity lead to distinct patterns of resurgent COVID-19 epidemics (either surges or endemic), which are observed in countries that implemented different COVID-19 health policies and achieved different vaccinated population plateaus after the vaccine rollouts in the first half of 2021.

Protein phosphorylation is a key regulatory mechanism in eukaryotic cells. In the intrinsically disordered histone tails, phosphorylation is often a part of combinatorial post-translational modifications and an integral part of the “histone code” that regulates gene expression. Here, we study the association between two histone H3 tail peptides modified to different degrees, using fully atomistic molecular dynamics simulations. Assuming that the initial conformations are either α-helical or fully extended, we compare the propensity of the two peptides to associate with one another when both are unmodified, one modified and the other unmodified, or both modified. The simulations lead to the identification of distinct inter- and intramolecular interactions in the peptide dimer, highlighting a prominent role of a fine-tuned phosphorylation rheostat in peptide association. Progressive phosphorylation appears to modulate peptide charge, inducing strong and specific intermolecular interactions between the monomers, which do not result in the formation of amorphous or ordered aggregates, as documented by experimental evidence derived from Circular Dichroism and NMR spectroscopy. However, upon complete saturation of positive charges by phosphate groups, this effect is reversed: intramolecular interactions prevail and dimerization of zero-charge peptides is markedly reduced. These findings underscore the role of phosphorylation thresholds in the dynamics of intrinsically disordered proteins. Phosphorylation rheostats might account for the divergent effects of histone modifications on the modulation of chromatin structure.

Imaging electrostatic field around individual atoms or defective areas in monolayer 2D materials is crucial to understand their structural coordination. Here, the authors report local changes in specific atomic bonds and provide in-depth structural information of complex defective monolayer MoS2 and WS2 systems by 4D STEM.

The efficiency of a catalyst relies on the stability of intermediates on its surface. Here, the authors find that van der Waals interactions between acetate adsorbates on Au(110) provide a small but necessary energy contribution to stabilize the acetate and drive restructuring of the Au surface.

Chimeras and branching are two archetypical complex phenomena that appear in many physical systems; because of their different intrinsic dynamics, they delineate opposite non-trivial limits in the complexity of wave motion and present severe challenges in predicting chaotic and singular behavior in extended physical systems. We report on the long-term forecasting capability of Long Short-Term Memory (LSTM) and reservoir computing (RC) recurrent neural networks, when they are applied to the spatiotemporal evolution of turbulent chimeras in simulated arrays of coupled superconducting quantum interference devices (SQUIDs) or lasers, and branching in the electronic flow of two-dimensional graphene with random potential. We propose a new method in which we assign one LSTM network to each system node except for “observer” nodes which provide continual “ground truth” measurements as input; we refer to this method as “Observer LSTM” (OLSTM). We demonstrate that even a small number of observers greatly improves the data-driven (model-free) long-term forecasting capability of the LSTM networks and provide the framework for a consistent comparison between the RC and LSTM methods. We find that RC requires smaller training datasets than OLSTMs, but the latter require fewer observers. Both methods are benchmarked against Feed-Forward neural networks (FNNs), also trained to make predictions with observers (OFNNs).

The relative orientation (twist) of successive layers of stacked two-dimensional (2D) materials creates variations in the interlayer atomic registry. The variations often form a superlattice, called a moiré pattern, which can alter electronic properties. In this work we introduce a classification of the single-particle electronic structures that can occur in twisted stacks of 2D layers by characterizing them as “moiré molecules” or “moiré crystals.” The molecules generate localized electronic states and moiré flat bands, while the crystals are sometimes unconventional and produce electronic banding in the configuration basis. The underpinning of this classification is the duality between interlayer configuration and monolayer Bloch momentum in moiré Hamiltonians. We apply this understanding to diagrams of local electron density in untwisted geometries to produce intuitive and quantitative predictions of twistronic properties. We provide a conceptual introduction to this framework through a one-dimensional model, and then apply it to 2D twisted bilayers of the semimetal graphene, and of MoS_{2}, a representative material of the transition metal dichalcogenide family of semiconductors. This level of thorough understanding of twistronic phenomena is vital in the search for new material platforms for localized moiré electrons.

As they do not rely on the presence of any crystal symmetry, Weyl nodes are robust topological features of an electronic structure that can occur at any momentum and energy. Acting as sinks and sources of Berry curvature, Weyl nodes have been predicted to strongly affect the transverse electronic response, like in the anomalous Hall or Nernst effects. However, to observe large anomalous effects the Weyl nodes need to be close to or at the Fermi level, which implies the band structure must be tuned by an external parameter, e.g., chemical doping. Here we show that in a ferromagnetic metal tuning of the Weyl node energy and momentum can be achieved by rotation of the magnetization. First, taking as example the elementary magnet hcp-Co, we use electronic structure calculations based on density-functional theory to show that by canting the magnetization away from the easy axis, Weyl nodes can be driven exactly to the Fermi surface. Second, we show that the same phenomenology applies to the kagome ferromagnet Co_{3}Sn_{2}S_{2}, in which we additionally show how the dynamics in energy and momentum of the Weyl nodes affects the calculated anomalous Hall and Nernst conductivities. Our results highlight how the intrinsic magnetic anisotropy can be used to engineer Weyl physics.

Twisted bilayer graphene (TBLG) has emerged as an important platform for studying correlated phenomena, including unconventional superconductivity, in two-dimensional systems. The complexity of the atomic-scale structures in TBLG has made even the study of single-particle physics at low energies around the Fermi level, quite challenging. Our goal here is to provide a convenient and physically motivated picture of single-particle physics in TBLG using reduced models with the smallest possible number of localized orbitals. The reduced models exactly reproduce the low-energy bands of ab initio tight-binding models, including the effects of atomic relaxations. Furthermore, we obtain for the first time the corresponding Wannier orbitals that incorporate all symmetries of TBLG, which are also calculated as a function of angle, a requisite first step towards incorporating electron interaction effects. We construct eight-band and five-band models for the low-energy states for twist angles between 1.3^{∘} and 0.6^{∘}. The models are created using a multistep Wannier projection technique starting with appropriate ab initio k·p continuum Hamiltonians. Our procedure can also readily capture the perturbative effects of substrates and external displacement fields while offering a significant reduction in complexity for studying electron-electron correlation phenomena in realistic situations.

We introduce a complete physical model for the single-particle electronic structure of twisted bilayer graphene (TBLG), which incorporates the crucial role of lattice relaxation. Our model, based on k·p perturbation theory and openly available, combines the accuracy of density functional theory calculations through effective tight-binding Hamiltonians with the computational efficiency and complete control of the twist angle offered by continuum models. The inclusion of relaxation significantly changes the band structure at the first magic-angle twist corresponding to flat bands near the Fermi level (the “low-energy” states), and eliminates the appearance of a second magic-angle twist. We show that minimal models for the low-energy states of TBLG can be easily modified to capture the changes in electronic states as a function of twist angle.