相关论文: Exploring magnetized liner inertial fusion with a …
Magnetic reconnection in partially ionized plasmas plays a crucial role in a wide range of solar, astrophysical, and laboratory environments. While reconnection in such plasmas is commonly characterized by the ion-neutral coupling strength…
A formulation of the effective hybridization model is developed which describes Fermi-liquid Kondo and fractionalized Fermi-liquid (deconfinement spin-liquid-like) states with account of possible magnetic ordering. A unified consideration…
Theoretical foundations and applications of the generalized spin-fermion (sp-d) exchange lattice model to various magnetic systems, e.g. rare-earth metals and compounds and magnetic semiconductors are discussed. The capabilities of the…
In three-dimensional magnetic configurations for a plasma in which no closed field line or magnetic null exists, no magnetic reconnection can occur, by the strictest definition of reconnection. A finitely long pinch with line-tied boundary…
To enhance the core heating efficiency in fast ignition laser fusion, the concept of relativistic electron beam guiding by external magnetic fields was evaluated by integrated simulations for FIREX class targets. For the cone-attached shell…
The recent progress of using graph based encoding of crystal structures for high throughput material property prediction has been quite successful. However, using a single modality model prevents us from exploiting the advantages of an…
MIF approaches, such as the MagLIF experiment, use magnetic fields in dense plasma to suppress cross-field thermal conduction, attempting to reduce heat losses and trap alpha particles to achieve ignition. However, the magnetic field can…
Renaissance Fusion proposes thick liquid metal walls as plasma-facing components for future commercial fusion reactors. It designs and operates proof-of-concept experiments aiming at actively suspending and stabilizing a flowing…
Machine learning plays an increasingly important role in computational chemistry and materials science, complementing computationally intensive ab initio and first-principles methods. Despite their utility, machine-learning models often…
Spin-polarized fusion has the potential to lower the radiation shielding and ignition requirements for fusion rockets while simultaneously increasing the fusion fuel burnup and provide better momentum coupling to a spacecraft. This…
Recent experiments at the National Ignition Facility (NIF) have demonstrated ignition for the first time in an inertial confinement fusion (ICF) experiment, a major milestone allowing the possibility of high energy gain through burn…
We present a machine-learning guided approach to predict saturation magnetization (MS) and coercivity (HC) in Fe-rich soft magnetic alloys, particularly Fe-Si-B systems. ML models trained on experimental data reveals that increasing Si and…
Motivated by breakthroughs in inertial confinement fusion (ICF), first achieving ignition conditions in National Ignition Facility (NIF) shot N210808 and then laser energy breakeven in N221204, modeling efforts here investigate the effect…
The behavior of magnetic field lines in a turbulent plasma is a key property of the medium, with important consequences for plasma dynamics and charged-particle transport. We study the diffusion properties of magnetic field lines in…
We present a computational framework for the simulations of powder-bed fusion of metallic alloys, which combines: (1) CalPhaD calculations of temperature-dependent alloy properties and phase diagrams, (2) macroscale finite element (FE)…
Machine learning interatomic potentials (MLIPs) require generating computationally expensive, large-scale training datasets to accurately simulate materials and molecules. Incorporating electronic structure information using multitask…
We investigate thermal Hall transport in magnetic systems, using semiclassical spin dynamics simulations. Building on a linear response framework, we discuss the intricacies of computing the thermal Hall conductivity from real-time energy…
Additive manufacturing (AM) offers an unprecedented opportunity for the quick production of complex shaped parts directly from a powder precursor. But its application to functional materials in general and magnetic materials in particular…
Rapid growth of machine learning methodologies and their applications offer new opportunity for improved transformer asset management. Accordingly, power system operators are currently looking for data-driven methods to make better-informed…
An experimental program is currently underway at the National Ignition Facility (NIF) to compress deuterium and tritium (DT) fuel to densities and temperatures sufficient to achieve fusion and energy gain. The primary approach being…