Antiferromagnets (AFMs) with zero net magnetization are proposed as active elements in future spintronic devices. Depending on the critical thickness of the AFM thin films and the measurement temperature, bimetallic Mn-based alloys and transition met
al oxide-based AFMs can host various coexisting ordered, disordered, and frustrated AFM phases. Such coexisting phases in the exchange coupled ferromagnetic (FM)/AFM-based heterostructures can result in unusual magnetic and magnetotransport phenomena. Here, we integrate chemically disordered AFM IrMn3 thin films with coexisting AFM phases into complex exchange coupled MgO(001)/Ni3Fe/IrMn3/Ni3Fe/CoO heterostructures and study the structural, magnetic, and magnetotransport properties in various magnetic field cooling states. In particular, we unveil the impact of rotating the relative orientation of the disordered and reversible AFM moments with respect to the irreversible AFM moments on the magnetic and magnetoresistance properties of the exchange coupled heterostructures. We further found that the persistence of AFM grains with thermally disordered and reversible AFM order is crucial for achieving highly tunable magnetic properties and multi-level magnetoresistance states. We anticipate that the introduced approach and the heterostructure architecture can be utilized in future spintronic devices to manipulate the thermally disordered and reversible AFM order at the nanoscale.
Antimony sulfide (Sb2S3) and selenide (Sb2Se3) have emerged as promising earth-abundant alternatives among thin-film photovoltaic compounds. A distinguishing feature of these materials is their anisotropic crystal structures, which are composed of qu
asi-one-dimensional (1D) [Sb4X6]n ribbons. The interaction between ribbons has been reported to be van der Waals (vdW) in nature and Sb2X3 are thus commonly classified in the literature as 1D semiconductors. However, based on first-principles calculations, here we show that inter-ribbon interactions are present in Sb2X3 beyond the vdW regime. The origin of the anisotropic structures is related to the stereochemical activity of the Sb 5s lone pair according to electronic structure analysis. The impacts of structural anisotropy on the electronic and optical properties are further examined, including the presence of higher dimensional Fermi surfaces for charge carrier transport. Our study provides guidelines for optimising the performance of Sb2X3-based solar cells via device structuring based on the underlying crystal anisotropy.
PtSe2 is attracting considerable attention as a high mobility two-dimensional material with envisionned applications in microelectronics, photodetection and spintronics. The growth of high quality PtSe2 on insulating substrates with wafer-scale unifo
rmity is a prerequisite for electronic transport investigations and practical use in devices. Here, we report the growth of highly oriented few-layers PtSe2 on ZnO(0001) by molecular beam epitaxy. The crystalline structure of the films is characterized with electron and X-ray diffraction, atomic force microscopy and transmission electron microscopy. The comparison with PtSe2 layers grown on graphene, sapphire, mica, SiO2 and Pt(111) shows that among insulating substrates, ZnO(0001) yields films of superior structural quality. Hall measurements performed on epitaxial ZnO/PtSe2 with 5 monolayers of PtSe2 show a clear semiconducting behaviour and a high mobility in excess of 200 cm2V 1s-1 at room temperature and up to 447 cm2V-1s-1 at low temperature.
We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal-organic framework (MOF) literature describing structurally characterized MOFs and their solvent removal and thermal stabilities. We ob
tain over 2,000 solvent removal stability measures from text mining and 3,000 thermal decomposition temperatures from thermogravimetric analysis data. We assess the validity of our NLP methods and the accuracy of our extracted data by comparing to a hand-labeled subset. Machine learning (ML, i.e. artificial neural network) models trained on this data using graph- and pore-geometry-based representations enable prediction of stability on new MOFs with quantified uncertainty. Our web interface, MOFSimplify, provides users access to our curated data and enables them to harness that data for predictions on new MOFs. MOFSimplify also encourages community feedback on existing data and on ML model predictions for community-based active learning for improved MOF stability models.
The type-II terminated 1T-TaS$_2$ surface of a three-dimensional 1T-TaS$_2$ bulk material realizes the effective spin-1/2 degree of freedom on each David-star cluster with ${T^2=-1}$ such that the time reversal symmetry is realized anomalously, despi
te the bulk three-dimensional 1T-TaS$_2$ material has an even number of electrons per unit cell with ${T^2=+1}$. This surface is effectively viewed as a spin-1/2 triangular lattice magnet, except with a symmetry-protected topological bulk. We further propose this surface termination realizes a spinon Fermi surface spin liquid with the surface fractionalization but with a non-exotic three-dimensional bulk. We analyze possible experimental consequences of the type-II terminated surface spin liquid.
A notable phenomenon in topological semimetals is the violation of Kohler$^,$s rule, which dictates that the magnetoresistance $MR$ obeys a scaling behavior of $MR = f(H/rho_0$), where $MR = [rho_H-rho_0]/rho_0$ and $H$ is the magnetic field, with $r
ho_H$ and $rho_0$ being the resistivity at $H$ and zero field, respectively. Here we report a violation originating from thermally-induced change in the carrier density. We find that the magnetoresistance of the Weyl semimetal, TaP, follows an extended Kohler$^,$s rule $MR = f[H/(n_Trho_0)]$, with $n_T$ describing the temperature dependence of the carrier density. We show that $n_T$ is associated with the Fermi level and the dispersion relation of the semimetal, providing a new way to reveal information on the electronic bandstructure. We offer a fundamental understanding of the violation and validity of Kohler$^,$s rule in terms of different temperature-responses of $n_T$. We apply our extended Kohler$^,$s rule to BaFe$_2$(As$_{1-x}$P$_x$)$_2$ to settle a long-standing debate on the scaling behavior of the normal-state magnetoresistance of a superconductor, namely, $MR$ ~ $tan^2theta_H$, where $theta_H$ is the Hall angle. We further validate the extended Kohler$^,$s rule and demonstrate its generality in a semiconductor, InSb, where the temperature-dependent carrier density can be reliably determined both theoretically and experimentally.
Heterostructures including the members of the 6.1{AA} semiconductor family (AlSb, GaSb, and InAs) are used in infrared optoelectronic devices as well as a variety of other applications. Short-period superlattices of these materials are also of intere
st for creating composite materials with designer infrared dielectric functions. The conditions needed to create sharp InAs/GaSb and InAs/AlSb interfaces are well known, but the AlSb/GaSb interface is much less well-understood. In this article, we test a variety of interventions designed to improve interface sharpness in AlSb/GaSb short-period superlattices. These interventions include substrate temperature, III:Sb flux ratio, and the use of a bismuth surfactant. Superlattices are characterized by high-resolution x-ray diffraction and infrared spectroscopy. We find that AlSb/GaSb short-period superlattices have a wide growth window over which sharp interfaces can be obtained.
Most metallic and ceramic materials are comprised of a space-filling collection of crystalline grains separated by grain boundaries. While this grain structure has been studied for more than a century, there few rigorous results regarding its global
properties available in the literature. We present a new, rigorous result for three-dimensional grain structures that relates the integral of the Gaussian curvature over the grain boundaries to the numbers of grains and quadruple junctions. The result is numerically verified for a grain structure consisting of periodic truncated octahedra.
Polarized neutron reflectometry (PNR) is a powerful technique to interrogate the structures of multilayered magnetic materials with depth sensitivity and nanometer resolution. However, reflectometry profiles often inhabit a complicated objective func
tion landscape using traditional fitting methods, posing a significant challenge to parameter retrieval. In this work, we develop a data-driven framework to recover the sample parameters from PNR data with minimal user intervention. We train a variational autoencoder to map reflectometry profiles with moderate experimental noise to an interpretable, low-dimensional space from which sample parameters can be extracted with high resolution. We apply our method to recover the scattering length density profiles of the topological insulator (TI)-ferromagnetic insulator heterostructure Bi$_2$Se$_3$/EuS, exhibiting proximity magnetism, in good agreement with the results of conventional fitting. We further analyze a more challenging PNR profile of the TI-antiferromagnet heterostructure (Bi,Sb)$_2$Te$_3$/Cr$_2$O$_3$, and identify possible interfacial proximity magnetism in this material. We anticipate the framework developed here can be applied to resolve hidden interfacial phenomena in a broad range of layered systems.
The growth of connected intelligent devices in the Internet of Things has created a pressing need for real-time processing and understanding of large volumes of analogue data. The difficulty in boosting the computing speed renders digital computing u
nable to meet the demand for processing analogue information that is intrinsically continuous in magnitude and time. By utilizing a continuous data representation in a nanoscale crossbar array, parallel computing can be implemented for the direct processing of analogue information in real time. Here, we propose a scalable massively parallel computing scheme by exploiting a continuous-time data representation and frequency multiplexing in a nanoscale crossbar array. This computing scheme enables the parallel reading of stored data and the one-shot operation of matrix-matrix multiplications in the crossbar array. Furthermore, we achieve the one-shot recognition of 16 letter images based on two physically interconnected crossbar arrays and demonstrate that the processing and modulation of analogue information can be simultaneously performed in a memristive crossbar array.
