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The giant spin–orbit torque (SOT) generated by topological surface states in topological insulators (TIs) provides an energy-efficient writing method for magnetic memory. In this study, we demonstrate a topological insulator/spin valve (TI/SV) device that operates at room temperature. An ultrathin, high-quality TI (Bi0.5Sb0.5)2Te3 (BST) thin film is epitaxially grown as a functional layer on a (0001)-Al2O3 substrate via molecular beam epitaxy in ultrahigh vacuum. Subsequently, Ta/CoFe/Cu/CoFe/IrMn layers are grown on BST/Al2O3 thin films using magnetron sputtering to form TI/SV devices via a subsequent standard lithography process. The resulting TI/SV devices exhibit a giant magnetoresistance of up to ∼1.1% at room temperature. Additionally, a low switching current density of approximately 1.25 × 105 A cm−2 is achieved, which implies high potential for further reducing the energy consumption of SOT-based devices. The SOT conversion efficiency and charge-spin conversion efficiency of the TI layer are approximately 4.74 × 10−6 Oe A−1 cm2 and 1.33, respectively, as extracted from the SOT-induced shift of the magnetic switching field. Moreover, the switching current density reduces steadily with the device size scaling down. This study can facilitate the realization of energy-efficient magnetic memory devices in the future. [ABSTRACT FROM AUTHOR]

Mixed-dimensional van der Waals (vdW) heterostructures, integrated two-dimensional (2D) atomic crystals with three-dimensional (3D) functional materials, offer a powerful means to manipulating physical properties and generating unprecedented functionalities. Understanding interfacial couplings at those hetero (homo)-interfaces is indispensable for exploring new optical and electronic devices. Herein, we investigated dynamically phase-transition-driven strain coupling across a vdW heterointerface through integrating 2D layered 2H-MoS2 nanoflakes onto 3D phase-change VO2 epitaxial thin films. The Raman peak positions of the in-plane and out-of-plane vibration modes E 2 g 1 and A1g from the 2H-MoS2 nanoflakes show a phonon softening and reversible hysteresis loop as a function of temperature in this mixed-dimensional vdW 2H-MoS2/( 1 ¯ 11)-VO2/(1 1 ¯ 02)-Al2O3 heterostructure, originating from the co-action of temperature-dependent anharmonicity in 2H-MoS2 and reversible structural phase transition (SPT)-induced in-plane tensile strain from the VO2 thin film. Accordingly, the integrated Raman scattering intensity of these two feature peaks of the 2H-MoS2 nanoflakes increased (decreased) as the temperature increased (decreased), exhibiting a hysteresis loop in the SPT and metal–insulator transition region of VO2. Additionally, the peak integrated intensity enhancement ratio of the E 2 g 1 and A1g vibration modes was approximately 2.3 and 2.8, respectively. These results indicate that the dynamically SPT-driven in-plane tensile strain from the bottom VO2 layer interfacially couples with the adjacent 2H-MoS2 nanoflakes and results in a reduction in the electronic transition energy, leading to an enhancement in the Raman scattering intensity of 2H-MoS2. Our work holds promise for dynamic strain control of lattice dynamics and electron–phonon interaction of 2D materials for functional electronic and photoelectronic devices. [ABSTRACT FROM AUTHOR]

De novo lipogenesis (DNL), a hallmark of cancer, facilitates tumor growth and metastasis. Therapeutic drugs targeting DNL are being developed. However, how DNL is directly regulated in cancer remains largely unknown. Here, transcription factor sine oculis homeobox 1 (SIX1) is shown to directly increase the expression of DNL-related genes, including ATP citrate lyase (ACLY), fatty acid synthase (FASN), and stearoyl-CoA desaturase 1 (SCD1), via histone acetyltransferases amplified in breast cancer 1 (AIB1) and lysine acetyltransferase 7 （HBO1/KAT7）, thus promoting lipogenesis. SIX1 expression is regulated by insulin/lncRNA DGUOK-AS1/microRNA-145-5p axis, which also modulates DNL-related gene expression as well as DNL. The DGUOK-AS1/microRNA-145-5p/SIX1 axis regulates liver cancer cell proliferation, invasion, and metastasis in vitro and in vivo. In patients with liver cancer, SIX1 expression is positively correlated with DGUOK-AS1 and SCD1 expression and is negatively correlated with microRNA-145-5p expression. DGUOK-AS1 is a good predictor of prognosis. Thus, the DGUOK-AS1/microRNA-145-5p/SIX1 axis strongly links DNL to tumor growth and metastasis and may become an avenue for liver cancer therapeutic intervention., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

As a quasi-layered ferrimagnetic material, Mn 3 Si 2 Te 6 nanoflakes exhibit magnetoresistance behavior that is fundamentally different from their bulk crystal counterparts. They offer three key properties crucial for spintronics. First, at least 10 6 times faster response compared to that exhibited by bulk crystals has been observed in current-controlled resistance and magnetoresistance. Second, ultralow current density is required for resistance modulation (∼5 A/cm 2 ). Third, electrically gate-tunable magnetoresistance has been realized. Theoretical calculations reveal that the unique magnetoresistance behavior in the Mn 3 Si 2 Te 6 nanoflakes arises from a magnetic field induced band gap shift across the Fermi level. The rapid current induced resistance variation is attributed to spin-orbit torque, an intrinsically ultrafast process (∼nanoseconds). This study suggests promising avenues for spintronic applications. In addition, it highlights Mn 3 Si 2 Te 6 nanoflakes as a suitable platform for investigating the intriguing physics underlying chiral orbital moments, magnetic field induced band variation, and spin torque.

This paper proposes a fluid classifier for a tight reservoir using a quantum neural network (QNN). It is difficult to identify the fluid in tight reservoirs, and the manual interpretation of logging data, which is an important means to identify the fluid properties, has the disadvantages of a low recognition rate and non-intelligence, and an intelligent algorithm can better identify the fluid. For tight reservoirs, the logging response characteristics of different fluid properties and the sensitivity and relevance of well log parameter and rock physics parameters to fluid identification are analyzed, and different sets of input parameters for fluid identification are constructed. On the basis of quantum neural networks, a new method for combining sample quantum state descriptions, sensitivity analysis of input parameters, and wavelet activation functions for optimization is proposed. The results of identifying the dry layer, gas layer, and gas-water co-layer in the tight reservoir in the Sichuan Basin of China show that different input parameters and activation functions affect recognition performance. The proposed quantum neural network based on hybrid parameters and a wavelet activation function has higher fluid identification accuracy than the original quantum neural network model, indicating that this method is effective and warrants promotion and application., (© 2024. The Author(s).)