Related papers: Elucidating proximity magnetism through polarized …
By adjusting the incidence angle of incoming X-ray near the critical angle of X-ray total reflection, the photoelectron intensity is strongly modulated due to the variation of X-ray penetration depth. Photoelectron spectroscopy (PES)…
Accurate characterization of polarization dependent light matter interactions in nanostructured systems is paramount for the development of chiral metasurfaces. It is also often challenging, because multiple anisotropic mechanisms, such as…
Reconstructing the structure of thin films and multilayers from measurements of scattered X-rays or neutrons is key to progress in physics, chemistry, and biology. However, finding all structures compatible with reflectometry data is…
Negative refraction provides an attractive platform to manipulate mid-infrared and terahertz radiation for molecular sensing and thermal radiation applications. However, its implementation based on available metamaterials and plasmonic…
This paper presents a method, namely NeuS-PIR, for recovering relightable neural surfaces using pre-integrated rendering from multi-view images or video. Unlike methods based on NeRF and discrete meshes, our method utilizes implicit neural…
Magnetic complex-oxide heterostructures are of keen interest because a wealth of phenomena at the interface of dissimilar materials can give rise to fundamentally new physics and potentially valuable functionalities. Altered magnetization,…
Neutron reflectivity is a powerful technique for probing density profiles in films, with applications across Physics, Chemistry, and Biology. However, challenges arise when dealing with samples characterized by high roughness, unknown…
Functional devices with ultrathin ferroelectric layers have been attracted as a promising candidate for next-generation memory and logic device applications. Using the ultrathin ferroelectric layers, particularly approaching the…
Accurately measuring the geometry and spatially-varying reflectance of real-world objects is a complex task due to their intricate shapes formed by concave features, hollow engravings and diverse surfaces, resulting in inter-reflection and…
Introducing magnetic order into a topological insulator (TI) system has been attracting much attention with an expectation of realizing exotic phenomena such as quantum anomalous Hall effect (QAHE) or axion insulator states. The magnetic…
Due to the lack of phase information, determining the physical parameters of multilayer thin films from measured neutron and X-ray reflectivity curves is, on a fundamental level, an underdetermined inverse problem. This so-called phase…
We present x-ray resonant magnetic reflectivity (XRMR) as a very sensitive tool to detect proximity induced interface spin polarization in Pt/Fe, Pt/Ni$_{33}$Fe$_{67}$, Pt/Ni$_{81}$Fe$_{19}$ (permalloy), and Pt/Ni bilayers. We demonstrate…
The parameter retrieval is a procedure in which effective material properties are assigned to a given metamaterial. A widely used technique bases on the inversion of reflection and transmission from a metamaterial slab. Thus far, local…
The ever increasing need for product advancement and miniaturization keeps thin film assemblies, membranes, magnetic and non-magnetic multilayer and patterned heterostructures in the limelight of material science and technological…
Neural implicit methods have achieved high-quality 3D object surfaces under slight specular highlights. However, high specular reflections (HSR) often appear in front of target objects when we capture them through glasses. The complex…
We present a new Bayesian methodology to learn the unknown material density of a given sample by inverting its two-dimensional images that are taken with a Scanning Electron Microscope. An image results from a sequence of projections of the…
We present a general framework for modeling power magnetic materials characteristics using deep neural networks. Magnetic materials represented by multidimensional characteristics (that mimic measurements) are used to train the neural…
We present a neural rendering-based method called NeRO for reconstructing the geometry and the BRDF of reflective objects from multiview images captured in an unknown environment. Multiview reconstruction of reflective objects is extremely…
Node embedding learns low-dimensional vectors for nodes in the graph. Recent state-of-the-art embedding approaches take Personalized PageRank (PPR) as the proximity measure and factorize the PPR matrix or its adaptation to generate…
Neutron reflectometry analysis is an inherently ill-posed, which is to say that there are many possible solutions which agree equally well with the measured data. This leads to the application of model-dependent analysis, where information…