Search for: All records

The anomalous Hall effect (AHE) is an efficient tool for detecting the Néel vector in collinear compensated magnets with spin-split bands, known as altermagnets (AMs). Here, we establish design principles for obtaining nonzero anomalous Hall conductivity in the recently proposed two-dimensional (2D) AMs using spin and magnetic group symmetry analysis. We show that only two of the seven nontrivial spin layer groups exhibit an unconventional in-plane AHE in which the Néel vector lies within the plane of the Hall current. Through first-principles simulations on bilayers of MnPSe3 and MnSe, we demonstrate the validity of our group theoretic framework for obtaining AHE with d- and i-wave altermagnetic orders, depending on the stacking of the bilayers. We find that the spin group symmetry is successful in determining the linear and cubic dependence of anomalous Hall conductivity in Néel vector space, although AHE is a relativistic effect. This work shows that the AHE in 2D AMs can probe the altermagnetic order and Néel vector reversal, thereby facilitating the miniaturization of altermagnetic spintronics. 

Spin-active defects in silicon carbide (SiC) are promising quantum light sources for realizing scalable quantum technologies. In different applications, these photoluminescent defects are often placed in a nanostructured host or close to surfaces in order to enhance the signal from the defects. However, proximity to the surface not only modifies the frequencies of the quantum emission from the defect, but also adversely affects their photostability, resulting in blinking and/or photobleaching of the defect. These effects can be ameliorated by passivating surfaces with optimal adsorbates. In this work, we explore different passivation schemes using density-functional-theory-based calculations. We show that a uniform surface passivation with either hydrogen or with mixed hydrogen/hydroxyl groups completely removes surface states from the SiC band gap, restoring the optical properties of the defects. 

Chemical modifications and/or simple vertical stacking of disparate van der Waals layered crystals can be used as a materials design approach for creating novel phases of matter. Here, using ab initio computations, we demonstrate the realization of an unusual state in a bismuth nanoribbon decorated with nitrogen atoms along one of the edges. In this phase, the quantum spin Hall state on one edge of the nanoribbon coexists with the ferromagnetism on the other edge. Such a coexistence is made possible by the short-range nature of the exchange interactions on the magnetic edge. As a result, the quantum spin Hall state on the opposite edge of the nanoribbon does not feel the local breaking of time-reversal symmetry on the magnetic edge. While the edge with quantum spin Hall state exhibits the typical spin-helical texture associated with the state, the magnetic edge displays ±k-asymmetry due to the interplay of Rashba and exchange effects. The latter is also a half-metal and can generate a fully spin-polarized current. We demonstrate that this coexistence of states is robust and that it is exhibited even when the nitrogen-decorated nanoribbon is placed on a substrate. In addition, with a proof-of-principle heterostructure, composed of an undecorated bismuth nanoribbon on hexagonal boron nitride, we show that this mixture of states can potentially exist even without passivation with nitrogen-atoms. In the heterostructure, an unequal relaxation along the two edges of the nanoribbon is found to be responsible for the coexistence of two states. 

Computing landscape is evolving rapidly. Exascale computers have arrived, which can perform 10^18 mathematical operations per second. At the same time, quantum supremacy has been demonstrated, where quantum computers have outperformed these fastest supercomputers for certain problems. Meanwhile, artificial intelligence (AI) is transforming every aspect of science and engineering. A highly anticipated application of the emerging nexus of exascale computing, quantum computing and AI is computational design of new materials with desired functionalities, which has been the elusive goal of the federal materials genome initiative. The rapid change in computing landscape resulting from these developments has not been matched by pedagogical developments needed to train the next generation of materials engineering cyberworkforce. This gap in curricula across colleges and universities offers a unique opportunity to create educational tools, enabling a decentralized training of cyberworkforce. To achieve this, we have developed training modules for a new generation of quantum materials simulator, named AIQ-XMaS (AI and quantum-computing enabled exascale materials simulator), which integrates exascalable quantum, reactive and neural-network molecular dynamics simulations with unique AI and quantum-computing capabilities to study a wide range of materials and devices of high societal impact such as optoelectronics and health. As a singleentry access point to these training modules, we have also built a CyberMAGICS (cyber training on materials genome innovation for computational software) portal, which includes step-by-step instructions in Jupyter notebooks and associated tutorials, while providing online cloud service for those who do not have access to adequate computing platform. The modules are incorporated into our open-source AIQ-XMaS software suite as tutorial examples and are piloted in classroom and workshop settings to directly train many users at the University of Southern California (USC) and Howard University—one of the largest historically black colleges and universities (HBCUs), with a strong focus on underrepresented groups. In this paper, we summarize these educational developments, including findings from the first CyberMAGICS Workshop for Underrepresented Groups, along with an introduction to the AIQ-XMaS software suite. Our training modules also include a new generation of open programming languages for exascale computing (e.g., OpenMP target) and quantum computing (e.g., Qiskit) used in our scalable simulation and AI engines that underlie AIQ-XMaS. Our training modules essentially support unique dual-degree opportunities at USC in the emerging exa-quantum-AI era: Ph.D. in science or engineering, concurrently with MS in computer science specialized in high-performance computing and simulations, MS in quantum information science or MS in materials engineering with machine learning. The developed modular cyber-training pedagogy is applicable to broad engineering education at large. 

Abstract Mechanical stacking of two dissimilar materials often has surprising consequences for heterostructure behavior. In particular, a 2D electron gas (2DEG) is formed in the heterostructure of the topological crystalline insulator Pb_0.24Sn_0.76Te and graphene due to contact of a polar with a nonpolar surface and the resulting changes in electronic structure needed to avoid polar catastrophe. The spintronic properties of this heterostructure with non‐local spin valve devices are studied. This study observes spin‐momentum locking at lower temperatures that transitions to regular spin channel transport only at ≈40 K. Hanle spin precession measurements show a spin relaxation time as high as 2.18 ns. Density functional theory calculations confirm that the spin‐momentum locking is due to a giant Rashba effect in the material and that the phase transition is a Lifshitz transition. The theoretically predicted Lifshitz transition is further evident in the phase transition‐like behavior in the Landé g‐factor and spin relaxation time.