اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدSpin-lattice coupling induced weak dynamical magnetism in EuTiO_3 at high temperatures
105
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
EuTiO_3, which is a G-type antiferromagnet below T_N = 5.5 K, has some fascinating properties at high temperatures, suggesting that macroscopically hidden dynamically fluctuating weak magnetism exists at high temperatures. This conjecture is substantiated by magnetic field dependent magnetization measurements, which exhibit pronounced anomalies below 200 K becoming more distinctive with increasing magnetic field strength. Additional results from muon spin rotation (${mu}$SR) experiments provide evidence for weak fluctuating bulk magnetism induced by spin-lattice coupling which is strongly supported in increasing magnetic field.
قيم البحث
اقرأ أيضاً
Electron-phonon coupling, being one of the most important parameters governing the material evolution after ultrafast energy deposition, yet remains the most unexplored one. In this work, we applied the dynamical coupling approach to calculate the no
nadiabatic electron-ion energy exchange in nonequilibrium solids with the electronic temperature high above the atomic one. It was implemented into the tight-binding molecular dynamics code, and used to study electron-phonon coupling in various elemental metals. The developed approach is a universal scheme applicable to electronic temperatures up to a few electron-Volts, and to arbitrary atomic configuration and dynamics. We demonstrate that the calculated electron-ion (electron-phonon) coupling parameter agrees well with the available experimental data in high-electronic-temperature regime, validating the model. The following materials are studied here - fcc metals: Al, Ca, Ni, Cu, Sr, Y, Zr, Rh, Pd, Ag, Ir, Pt, Au, Pb; hcp metals: Mg, Sc, Ti, Co, Zn, Tc, Ru, Cd, Hf, Re, Os; bcc metals: V, Cr, Fe, Nb, Mo, Ba, Ta, W; diamond cubic lattice metals: Sn; specific cases of Ga, In, Mn, Te and Se; and additionally semimetal graphite and semiconductors Si and Ge. For many materials, we provide the first and so far the only estimation of the electron-phonon coupling at elevated electron temperatures, which can be used in various models simulating ultrafast energy deposition in matter. We also discuss the dependence of the coupling parameter on the atomic mass, temperature and density.
The discovery of an ever increasing family of atomic layered magnetic materials, together with the already established vast catalogue of strong spin-orbit coupling (SOC) and topological systems, calls for some guiding principles to tailor and optimiz
e novel spin transport and optical properties at their interfaces. Here we focus on the latest developments in both fields that have brought them closer together and make them ripe for future fruitful synergy. After outlining fundamentals on van der Waals (vdW) magnetism and SOC effects, we discuss how their coexistence, manipulation and competition could ultimately establish new ways to engineer robust spin textures and drive the generation and dynamics of spin current and magnetization switching in 2D materials-based vdW heterostructures. Grounding our analysis on existing experimental results and theoretical considerations, we draw a prospective analysis about how intertwined magnetism and spin-orbit torque (SOT) phenomena combine at interfaces with well-defined symmetries, and how this dictates the nature and figures-of-merit of SOT and angular momentum transfer. This will serve as a guiding role in designing future non-volatile memory devices that utilize the unique properties of 2D materials with the spin degree of freedom.
Structural as well as magnetization studies have been carried out on graphite samples irradiated by neutrons over 50 years in the CIRUS research reactor at Trombay. Neutron diffraction studies reveal that the defects in irradiated graphite samples ar
e not well annealed and remain significant up to high temperatures much greater than 653 K where the Wigner energy is completely released. We infer that the remnant defects may be intralayer Frenkel defects, which do not store large energy, unlike the interlayer Frenkel defects that store the Wigner energy. Magnetization studies on the irradiated graphite show ferromagnetic behavior even at 300 K and a large additional paramagnetic contribution at 5 K. Ab-initio calculations based on the spin-polarized density-functional theory show that the magnetism in defected graphite is essentially confined on to a single 2-coordinated carbon atom that is located around a vacancy in the hexagonal layer.
We have characterized the temperature dependence of the flux threading dc SQUIDs cooled to millikelvin temperatures. The flux increases as 1/T as temperature is lowered; moreover, the flux change is proportional to the density of trapped vortices. Th
e data is compatible with the thermal polarization of surface spins in the trapped fields of the vortices. In the absence of trapped flux, we observe evidence of spin-glass freezing at low temperature. These results suggest an explanation for the universal 1/f flux noise in SQUIDs and superconducting qubits.
High-temperature alloy design requires a concurrent consideration of multiple mechanisms at different length scales. We propose a workflow that couples highly relevant physics into machine learning (ML) to predict properties of complex high-temperatu
re alloys with an example of the 9-12 wt.% Cr steels yield strength. We have incorporated synthetic alloy features that capture microstructure and phase transformations into the dataset. Identified high impact features that affect yield strength of 9Cr from correlation analysis agree well with the generally accepted strengthening mechanism. As part of the verification process, the consistency of sub-datasets has been extensively evaluated with respect to temperature and then refined for the boundary conditions of trained ML models. The predicted yield strength of 9Cr steels using the ML models is in excellent agreement with experiments. The current approach introduces physically meaningful constraints in interrogating the trained ML models to predict properties of hypothetical alloys when applied to data-driven materials.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
