Search

Modeling inorganic glasses requires an accurate representation of interatomic interactions, large system sizes to allow for intermediate-range structural order, and slow quenching rates to eliminate kinetically trapped structural motifs. Neither first principles- nor force field-based molecular dynamics (MD) simulations satisfy these three criteria unequivocally. Herein, we report the development of a machine learning potential (MLP) for a classic glass, B$_2$O$_3$, which meets these goals well. The MLP is trained on condensed phase configurations whose energies and forces on the atoms are obtained using periodic quantum density functional theory. Deep potential MD (DPMD) simulations based on this MLP accurately predict the equation of state and the densification of the glass with slower quenching from the melt. At ambient conditions, quenching rates larger than 10$^{11}$ K/s are shown to lead to artifacts in the structure. Pressure-dependent X-ray and neutron structure factors from the simulations compare excellently with experimental data. High-pressure simulations of the glass show varied coordination geometries of boron and oxygen, which concur with experimental observations., Comment: 15 pages, 11 figures

The kagome metal FeSn, consists of alternating layers of kagome-lattice Fe3Sn and honeycomb Sn2, and exhibits great potential for applications in future low energy electronics and spintronics because of an ideal combination of novel topological phases and high-temperature magnetic ordering. Robust synthesis methods for ultra-thin FeSn films, as well as an understanding of their air stability is crucial for its development and long-term operation in future devices. In this work, we realize large area, sub-10 nm epitaxial FeSn thin films, and explore the oxidation process via synchrotron-based photoelectron spectroscopy using in-situ oxygen and water dosing, as well as ex-situ air exposure. Upon exposure to atmosphere the FeSn films are shown to be highly reactive, with a stable ~3 nm thick oxide layer forming at the surface within 10 minutes. Notably the surface Fe remains largely unoxidized when compared to Sn, which undergoes near-complete oxidation. This is further confirmed with controlled in-situ dosing of O2 and H2O where only the Sn2 (stanene) inter-layers within the FeSn lattice oxidize, suggesting the Fe3Sn kagome layers remain almost pristine. These results are in excellent agreement with first principles calculations, which show Fe-O bonds to the Fe3Sn layer are energetically unfavorable, and furthermore, a large formation energy preference of 1.37 eV for Sn-O bonds in the stanene Sn2 layer over Sn-O bonds in the kagome Fe3Sn layer. The demonstration that oxidation only occurs within the stanene layers may provide new avenues in how to engineer, handle and prepare future kagome metal devices., Comment: 21 pages, 5 figures, 4 SI figures

Quantum dots (QD) with electric-field-controlled charge state are promising for electronics applications, e.g., digital information storage, single-electron transistors and quantum computing. Inorganic QDs consisting of semiconductor nanostructures or heterostructures often offer limited control on size and composition distribution, as well as low potential for scalability and/or nanoscale miniaturization. Owing to their tunability and self-assembly capability, using organic molecules as building nano-units can allow for bottom-up synthesis of two-dimensional (2D) nanoarrays of QDs. However, 2D molecular self-assembly protocols are often applicable on metals surfaces, where electronic hybridization and Fermi level pinning can hinder electric-field control of the QD charge state. Here, we demonstrate the synthesis of a single-component self-assembled 2D array of molecules [9, 10-dicyanoanthracene (DCA)] that exhibit electric-field-controlled spatially periodic charging on a noble metal surface, Ag(111). The charge state of DCA can be altered (between neutral and negative), depending on its adsorption site, by the local electric field induced by a scanning tunneling microscope tip. Limited metal-molecule interactions result in an effective tunneling barrier between DCA and Ag(111) that enables electric-field-induced electron population of the lowest unoccupied molecular orbital (LUMO) and hence charging of the molecule. Subtle site-dependent variation of the molecular adsorption height translates into a significant spatial modulation of the molecular polarizability, dielectric constant and LUMO energy level alignment, giving rise to a spatially dependent effective molecule-surface tunneling barrier and likelihood of charging. This work offers potential for high-density 2D self-assembled nanoarrays of identical QDs whose charge states can be addressed individually with an electric field.

The integration of intrinsically magnetic and topologically nontrivial two-dimensional materials holds tantalizing prospects for the exotic quantum anomalous Hall insulators and magnetic second-order topological insulators (SOTIs). Compared with the well-studied nonmagnetic counterparts, the pursuit of intrinsic magnetic SOTIs remains limited. In this work, we address this gap by focusing on $p-d$ orbitals inversion, a fundamental but often overlooked phenomena in the construction of topological materials. We begin by developing a theoretical framework to elucidate $p-d$ orbitals inversion through a combined density-functional theory calculation and Wannier downfolding. Subsequently we showcase the generality of this concept in realizing ferromagnetism SOTIs by identifying two real materials with distinct lattices: 1$T$-VS$_2$ in a hexagonal lattice, and CrAs monolayer in a square lattice. We further compare it with other mechanisms requiring spin-orbit coupling and explore the similarities to topological Kondo insulators. Our findings establish a generic pathway towards intrinsic magnetic SOTIs., Comment: 4 figures, all comments are welcomed !

Given starting and ending positions and velocities, $L_2$ bounds on the acceleration and velocity, and the restriction to no more than two constant control inputs, this paper provides routines to compute the minimal-time path. Closed form solutions are provided for reaching a position in minimum time with and without a velocity bound, and for stopping at the goal position. A numeric solver is used to reach a goal position and velocity with no more than two constant control inputs. If a cruising phase at the terminal velocity is needed, this requires solving a non-linear equation with a single parameter. Code is provided on GitHub at https://github.com/RoboticSwarmControl/MinTimeL2pathsConstraints., Comment: 8 pages, 8 figures, accepted for presentation at ACC 2024, https://acc2024.a2c2.org/

Telemedicine applications have recently received substantial potential and interest, especially after the COVID-19 pandemic. Remote experience will help people get their complex surgery done or transfer knowledge to local surgeons, without the need to travel abroad. Even with breakthrough improvements in internet speeds, the delay in video streaming is still a hurdle in telemedicine applications. This imposes using image compression and region of interest (ROI) techniques to reduce the data size and transmission needs. This paper proposes a Deep Reinforcement Learning (DRL) model that intelligently adapts the ROI size and non-ROI quality depending on the estimated throughput. The delay and structural similarity index measure (SSIM) comparison are used to assess the DRL model. The comparison findings and the practical application reveal that DRL is capable of reducing the delay by 13% and keeping the overall quality in an acceptable range. Since the latency has been significantly reduced, these findings are a valuable enhancement to telemedicine applications., Comment: 7 pages

The diffusivity of water in aqueous cesium iodide solutions is larger than that in neat liquid water, and vice versa for sodium chloride solutions. Such peculiar ion-specific behavior, called anomalous diffusion, is not reproduced in typical force field-based molecular dynamics (MD) simulations due to inadequate treatment of ion-water interactions. Herein, this hurdle is tackled using machine learned atomic potentials (MLPs) trained on data from density functional theory calculations. MLP-based atomistic MD simulations of aqueous salt solutions reproduce experimentally determined thermodynamic, structural, dynamical, and transport properties, including their varied trends of water diffusivities across salt concentration. This enables an examination of their intermolecular structure to unravel the microscopic underpinnings of the distinction in their transport. While both ions in CsI solutions contribute to faster diffusion of water molecules, the competition between the heavy retardation by Na-ions and slight acceleration by Cl-ions in NaCl solutions reduces their water diffusivity., Comment: 23 pages, 5 figures

Spin-orbit torque (SOT) is receiving tremendous attention from both fundamental and application-oriented aspects. Co2MnGa, a Weyl ferromagnet that is in a class of topological quantum materials, possesses cubic-based high structural symmetry, the L21 crystal ordering, which should be incapable of hosting anisotropic SOT in conventional understanding. Here we show the discovery of a gigantic anisotropy of self-induced SOT in Co2MnGa. The magnitude of the SOT is comparable to that of heavy metal/ferromagnet bilayer systems despite the high inversion symmetry of the Co2MnGa structure. More surprisingly, a sign inversion of the self-induced SOT is observed for different crystal axes. This finding stems from the interplay of the topological nature of the electronic states and their strong modulation by external strain. Our research enriches the understanding of the physics of self-induced SOT and demonstrates a versatile method for tuning SOT efficiencies in a wide range of materials for topological and spintronic devices., Comment: 15pages, 4figures (To appear Nano Lett.)

Electron-electron interactions in materials lead to exotic many-body quantum phenomena including Mott metal-insulator transitions (MITs), magnetism, quantum spin liquids, and superconductivity. These phases depend on electronic band occupation and can be controlled via the chemical potential. Flat bands in two-dimensional (2D) and layered materials with a kagome lattice enhance electronic correlations. Although theoretically predicted, correlated-electron Mott insulating phases in monolayer 2D metal-organic frameworks (MOFs) with a kagome structure have not yet been realised experimentally. Here, we synthesise a 2D kagome MOF on a 2D insulator. Scanning tunnelling microscopy (STM) and spectroscopy reveal a MOF electronic energy gap of ~200 meV, consistent with dynamical mean field theory predictions of a Mott insulator. Combining template-induced (via work function variations of the substrate) and STM probe-induced gating, we locally tune the electron population of the MOF kagome bands and induce Mott MITs. These findings enable technologies based on electrostatic control of many-body quantum phases in 2D MOFs., Comment: 34 pages, 4 figures + SI 53 pages, 33 figures

Here we demonstrate the occurrence of robust itinerant ferromagnetism in Mott-Hubbard systems at both low and high doping concentrations. Specifically, we study the effect of hole doping on the experimentally synthesized LaCrAsO via first-principles calculations and observe that the parent G-type antiferromagnetism vanishes quickly at low doping concentration ($x$ $\sim$ 0.20) and the system becomes ferromagnetic metal due to the canonical double exchange (CDE) mechanism. As $x$ continues to increase, the onsite energy difference between Cr 3$d$ and As 4$p$ orbitals decreases and the system transitions to a ferromagnetic negative charge-transfer energy metal. Therefore, the itinerant ferromagnetism doesn't terminate at intermediate $x$ as CDE mechanism usually predicts. Furthermore, our calculations reveal that both nearest and next-nearest ferromagnetic exchange coupling strengths keep growing with $x$, showing that ferromagnetism caused by negative charge-transfer energy state is "stronger" than that of CDE picture. Our work not only unveils an alternative mechanism of itinerant ferromagnetism, but also has the potential to attract immediate interest among experimentalists., Comment: 6 pages, 3 figures, comments are welcomed

Tuning the interaction between the bulk and edge states of topological materials is a powerful tool for manipulating edge transport behavior, opening up exciting opportunities for novel electronic and spintronic applications. This approach is particularly suited to topological crystalline insulators (TCI), a class of topologically nontrivial compounds that are endowed with multiple degrees of topological protection. In this study, we investigate how bulk-edge interactions can influence the edge transport in planar bismuthene, a TCI with metallic edge states protected by in-plane mirror symmetry, using first principles calculations and symmetrized Wannier tight-binding models. By exploring the impact of various perturbation effects, such as device size, substrate potentials, and applied transverse electric field, we examine the evolution of the electronic structure and edge transport in planar bismuthene. Our findings demonstrate that the TCI states of planar bismuthene can be engineered to exhibit either a gapped or conducting unconventional helical spin texture via a combination of substrate and electric field effects. Furthermore, under strong electric fields, the edge states can be stabilized through a delicate control of the bulk-edge interactions. These results open up new directions for discovering novel spin transport patterns in topological materials and provide critical insights for the fabrication of topological spintronic devices., Comment: 23 pages, 8 figures

The high strength of structural aluminium alloys depends strongly on the controlled precipitation of specific intermetallic phases, whose identity and crystal structure can be difficult to predict. Here, we investigate the Al-Pt system, which shows some similarity to the Al-Cu system as one of their main intermetallic phases, $Al_2Pt$, is nearly isostructural with $\theta^{\prime} (Al_2Cu)$, the metastable phase responsible for the high-strength of Al-Cu alloys. However, phases in Al-Pt alloys are complex and have not been studied in detail. Using a combination of density-functional theory (DFT) calculations and classical nucleation theory (CNT) applied to the Al-Pt system, we design a workflow to predict the thermodynamics of solid solution, intermediate phases such as GP zones, stable and metastable precipitates, and their precipitation sequence. This workflow can be applied to an arbitrary binary alloying system. We confirm the known stable phases $Al_4Pt$, $Al_{21}Pt_8$, $Al_2Pt$, $Al_3Pt_2$, $AlPt (\alpha \& \beta)$, $Al_3Pt_5$, $AlPt_2 (\alpha \& \beta)$ and $AlPt_3 (\alpha \& \beta)$. We also reveal the possible existence of two phases of chemical formulae $Al_5Pt$ and $Al_3Pt$. This large number of intermetallic phases is due to the strong bonding between Al and Pt, which also leads to significant favourable Pt solute formation energy in the Al matrix. Our findings are compared with the known precipitation characteristics of the binary Al-Cu and Al-Au systems. We find that the $\theta^{\prime}$-like $Al_2Pt$ precipitate phase has a lower coherent interfacial energy than $\theta^{\prime}$. Our calculations strongly suggest that $Al_2Pt$ will precipitate first in Al-rich Al-Pt alloys and will form bulk-like interfaces similar to $\eta (Al_2Au)$ rather than like $\theta^{\prime}(Al_2Cu)$., Comment: 32 pages, 9 figures in the main text. 12 pages, 7 figures in the supplementary inforamtion

Shear viscosity, though being a fundamental property of all liquids, is computationally expensive to estimate from equilibrium molecular dynamics simulations. Recently, Machine Learning (ML) methods have been used to augment molecular simulations in many contexts, thus showing promise to estimate viscosity too in a relatively inexpensive manner. However, ML methods face significant challenges like overfitting when the size of the data set is small, as is the case with viscosity. In this work, we train several ML models to predict the shear viscosity of a Lennard-Jones (LJ) fluid, with particular emphasis on addressing issues arising from a small data set. Specifically, the issues related to model selection, performance estimation and uncertainty quantification were investigated. First, we show that the widely used performance estimation procedure of using a single unseen data set shows a wide variability on small data sets. In this context, the common practice of using Cross validation (CV) to select the hyperparameters (model selection) can be adapted to estimate the generalization error (performance estimation) as well. We compare two simple CV procedures for their ability to do both model selection and performance estimation, and find that k-fold CV based procedure shows a lower variance of error estimates. We discuss the role of performance metrics in training and evaluation. Finally, Gaussian Process Regression (GPR) and ensemble methods were used to estimate the uncertainty on individual predictions. The uncertainty estimates from GPR were also used to construct an applicability domain using which the ML models provided more reliable predictions on another small data set generated in this work. Overall, the procedures prescribed in this work, together, lead to robust ML models for small data sets., Comment: main: 17 pages, 11 figures ; SI: 55 pages, 29 figures ; to be submitted to Journal of Chemical Physics

Two-dimensional (2D) metal-organic frameworks (MOFs) in a kagome lattice can exhibit strong electron-electron interactions, which can lead to tunable quantum phases including many exotic magnetic phases. While technological developments of 2D MOFs typically take advantage of substrates for growth, support, and electrical contacts, investigations often ignore substrates and their dramatic influence on electronic properties of MOFs. Here, we show how substrates alter the correlated magnetic phases in kagome MOFs using systematic density functional theory and mean-field Hubbard calculations. We demonstrate that MOF-substrate coupling, MOF-substrate charge transfer, strain, and external electric fields are key variables, activating and deactivating magnetic phases in these materials. While we consider the example of kagome-arranged 9,10-dicyanoanthracene molecules coordinated with copper atoms, our findings should generalise to any kagome lattice. This work offers useful predictions for tunable interaction-induced magnetism in surface-supported 2D organic materials, opening the door to solid-state electronic and spintronic technologies based on such systems., Comment: 29 pages, 16 figures (including supplementary information). Clarified several of our arguments, added extra panels to Supplementary Figure 10, clarified some figure legends (results unchanged)

The application of ultrathin two-dimensional (2D) perovskites in near-infrared and visible-range optoelectronics has been limited owing to their inherent wide bandgaps, large excitonic binding energies and low optical absorption at higher wavelengths. Here, we show that by tailoring interfacial band alignments via conjugation with low-dimensional materials like monolayer transition metal dichalcogenides (TMD), the functionalities of 2D perovskites can be extended to diverse, visible-range photophysical applications. Based on the choice of individual constituents in the 2D perovskite/TMD heterostructures, our first principles calculations demonstrate widely tunable type-II band gaps, carrier effective masses and band offsets to enable an effective separation of photogenerated excitons for enhanced photodetection and photovoltaic applications. In addition, we show the possibilities of achieving a type-I band alignment for recombination based light emitters as well as a type-III configuration for tunnelling devices. Further, we evaluate the effect of strain on the electronic properties of the heterostructures to show a significant strain tolerance, making them prospective candidates in flexible photosensors., Comment: 38 pages, main manuscript and supporting information