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Coupling of spin and charge currents to structural chirality in non-magnetic materials, known as chirality-induced spin selectivity, is promising for application in spintronic devices at room temperature. Although the chirality-induced spin selectivity effect has been identified in various chiral materials, its Onsager reciprocal process, the inverse chirality-induced spin selectivity effect, remains unexplored. Here we report the observation of the inverse chirality-induced spin selectivity effect in chiral assemblies of π-conjugated polymers. Using spin-pumping techniques, the inverse chirality-induced spin selectivity effect enables quantification of the magnitude of the longitudinal spin-to-charge conversion driven by chirality-induced spin selectivity in different chiral polymers. By widely tuning conductivities and supramolecular chiral structures via a printing method, we found a very long spin relaxation time of up to several nanoseconds parallel to the chiral axis. Our demonstration of the inverse chirality-induced spin selectivity effect suggests possibilities for elucidating the puzzling interplay between spin and chirality, and opens a route for spintronic applications using printable chiral assemblies.
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Utilization of the interaction between spin and heat currents is the central focus of the field of spin caloritronics. Chiral phonons possessing angular momentum arising from the broken symmetry of a non-magnetic material create the potential for generating spin currents at room temperature in response to a thermal gradient, precluding the need for a ferromagnetic contact. Here we show the observation of spin currents generated by chiral phonons in a two-dimensional layered hybrid organic-inorganic perovskite implanted with chiral cations when subjected to a thermal gradient. The generated spin current shows a strong dependence on the chirality of the film and external magnetic fields, of which the coefficient is orders of magnitude larger than that produced by the reported spin Seebeck effect. Our findings indicate the potential of chiral phonons for spin caloritronic applications and offer a new route towards spin generation in the absence of magnetic materials.
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The understanding and manipulation of anisotropic Gilbert damping is crucial for both fundamental research and versatile engineering and optimization. Although several works on anisotropic damping have been reported, no direct relationship between the band structure and anisotropic damping was established. Here, we observed an anisotropic damping in Fe/GeTe manipulated by the symmetric band structures of GeTe via angle-resolved photoemission spectroscopy. Moreover, the anisotropic damping can be modified by the symmetry of band structures. Our Letter provides insightful understandings of the anisotropic Gilbert damping in ferromagnets interfaced with Rashba semiconductors and suggests the possibility of manipulating the Gilbert damping by band engineering.
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Device-level implementation of soft materials for energy conversion and thermal management demands a comprehensive understanding of their thermal conductivity and elastic modulus to mitigate thermo-mechanical challenges and ensure long-term stability. Thermal conductivity and elastic modulus are usually positively correlated in soft materials, such as amorphous macromolecules, which poses a challenge to discover materials that are either soft and thermally conductive or hard and thermally insulative. Here, we show anomalous correlations of thermal conductivity and elastic modulus in two-dimensional (2D) hybrid organic-inorganic perovskites (HOIP) by engineering the molecular interactions between organic cations. By replacing conventional alkyl-alkyl and aryl-aryl type organic interactions with mixed alkyl-aryl interactions, we observe an enhancement in elastic modulus with a reduction in thermal conductivity. This anomalous dependence provides a route to engineer thermal conductivity and elastic modulus independently and a guideline to search for better thermal management materials. Further, introducing chirality into the organic cation induces a molecular packing that leads to the same thermal conductivity and elastic modulus regardless of the composition across all half-chiral 2D HOIPs. This finding provides substantial leeway for further investigations in chiral 2D HOIPs to tune optoelectronic properties without compromising thermal and mechanical stability.
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The chiral induced spin selectivity (CISS) effect, in which the structural chirality of a material determines the preference for the transmission of electrons with one spin orientation over that of the other, is emerging as a design principle for creating next-generation spintronic devices. CISS implies that the spin preference of chiral structures persists upon injection of pure spin currents and can act as a spin analyzer without the need for a ferromagnet. Here, we report an anomalous spin current absorption in chiral metal oxides that manifests a colossal anisotropic nonlocal Gilbert damping with a maximum-to-minimum ratio of up to 1000%. A twofold symmetry of the damping is shown to result from differential spin transmission and backscattering that arise from chirality-induced spin splitting along the chiral axis. These studies reveal the rich interplay of chirality and spin dynamics and identify how chiral materials can be implemented to direct the transport of spin current.
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Exploratory synthesis has been the main generator of new inorganic materials for decades. However, our Edisonian and bias-prone processes of synthetic exploration alone are no longer sufficient in an age that demands rapid advances in materials development. In this work, we demonstrate an end-to-end attempt towards systematic, computer-aided discovery and laboratory synthesis of inorganic crystalline compounds as a modern alternative to purely exploratory synthesis. Our approach initializes materials discovery campaigns by autonomously mapping the synthetic feasibility of a chemical system using density functional theory with AI feedback. Following expert-driven down-selection of newly generated phases, we use solid-state synthesis and in situ characterization via hot-stage X-ray diffraction in order to realize new ternary oxide phases experimentally. We applied this strategy in six ternary transition-metal oxide chemistries previously considered well-explored, one of which culminated in the discovery of two novel phases of calcium ruthenates. Detailed characterization using room temperature X-ray powder diffraction, 4D-STEM and SQUID measurements identifies the structure and composition and confirms distinct properties, including distinct defect concentrations, of one of the new phases formed in our experimental campaigns. While the discovery of a new material guided by AI and DFT theory represents a milestone, our procedure and results also highlight a number of critical gaps in the process that can inform future efforts towards the improvement of AI-coupled methodologies.
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Nanosized perovskite ferroelectrics are widely employed in several electromechanical, photonics, and thermoelectric applications. Scaling of ferroelectric materials entails a severe reduction in the lattice (phonon) thermal conductivity, particularly at sub-100 nm length scales. Such thermal conductivity reduction can be accurately predicted using the information of phonon mean free path (MFP) distribution. The current understanding of phonon MFP distribution in perovskite ferroelectrics is still inconclusive despite the critical thermal management implications. Here, high-quality single-crystalline barium titanate (BTO) thin films, a representative perovskite ferroelectric material, are grown at several thicknesses. Using experimental thermal conductivity measurements and first-principles based modeling (including four-phonon scattering), the phonon MFP distribution is determined in BTO. The simulation results agree with the measured thickness-dependent thermal conductivity. The results show that the phonons with sub-100 nm MFP dominate the thermal transport in BTO, and phonons with MFP exceeding 10 nm contribute ≈35% to the total thermal conductivity, in significant contrast to previously published experimental results. The experimentally validated phonon MFP distribution is consistent with the theoretical predictions of other complex crystals with strong anharmonicity. This work paves the way for thermal management in nanostructured and ferroelectric-domain-engineered systems for oxide perovskite-based functional materials.
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Hybrid magnonic systems are a newcomer for pursuing coherent information processing owing to their rich quantum engineering functionalities. One prototypical example is hybrid magnonics in antiferromagnets with an easy-plane anisotropy that resembles a quantum-mechanically mixed two-level spin system through the coupling of acoustic and optical magnons. Generally, the coupling between these orthogonal modes is forbidden due to their opposite parity. Here we show that the Dzyaloshinskii-Moriya-Interaction (DMI), a chiral antisymmetric interaction that occurs in magnetic systems with low symmetry, can lift this restriction. We report that layered hybrid perovskite antiferromagnets with an interlayer DMI can lead to a strong intrinsic magnon-magnon coupling strength up to 0.24 GHz, which is four times greater than the dissipation rates of the acoustic/optical modes. Our work shows that the DMI in these hybrid antiferromagnets holds promise for leveraging magnon-magnon coupling by harnessing symmetry breaking in a highly tunable, solution-processable layered magnetic platform.
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OBJECTIVE: Pediatric functional nausea is challenging for patients to manage and for clinicians to treat since it lacks objective diagnosis and assessment. A data-driven non-invasive diagnostic screening tool that distinguishes the electro-pathophysiology of pediatric functional nausea from healthy controls would be an invaluable aid to support clinical decision-making in diagnosis and management of patient treatment methodology. The purpose of this paper is to present an innovative approach for objectively classifying pediatric functional nausea using cutaneous high-resolution electrogastrogram data. METHODS: We present an Automated Electrogastrogram Data Analytics Pipeline framework and demonstrate its use in a 3x8 factorial design to identify an optimal classification model according to a defined objective function. Low-fidelity synthetic high-resolution electrogastrogram data were generated to validate outputs and determine SOBI-ICA noise reduction effectiveness. RESULTS: A 10 parameter support vector machine binary classifier with a radial basis function kernel was selected as the overall top-performing model from a pool of over 1000 alternatives via maximization of an objective function. This resulted in a 91.6% test ROC AUC score. CONCLUSION: Using an automated machine learning pipeline approach to process high-resolution electrogastrogram data allows for clinically significant objective classification of pediatric functional nausea. SIGNIFICANCE: To our knowledge, this is the first study to demonstrate clinically significant performance in the objective classification of pediatric nausea patients from healthy control subjects using experimental high-resolution electrogastrogram data. These results indicate a promising potential for high-resolution electrogastrography to serve as a data-driven screening tool for the objective diagnosis of pediatric functional nausea.