BUSCADOR RECOLECTA

Digital.CSIC. Repositorio Institucional del CSIC

oai:digital.csic.es:10261/308389

The magneto-optical Kerr effect (MOKE) is a widely used lab-based technique for the study of thin films and nanostructures, providing magnetic characterization with good spatial and temporal resolutions. Due to the complex coupling of light with a magnetic sample, conventional MOKE magnetometers normally work by selecting a small range of incident wave-vector values, focusing the incident light beam to a small spot, and recording the reflected intensity at that angular range by means of photodetectors. This generally provides signals proportional to a mixture of magnetization components, requiring additional methodologies for full vectorial magnetic characterization. Here, we computationally investigate a Fourier-space MOKE setup, where a focused beam ellipsometer using high numerical aperture optics and a camera detector is employed to simultaneously map the intensity distribution for a wide range of incident and reflected wave-vectors. We employ circularly incident polarized light and no analyzing optics, in combination with a fitting procedure of the light intensity maps to the analytical expression of the Kerr effect under linear approximation. In this way, we are able to retrieve the three unknown components of the magnetization vector as well as the material's optical and magneto-optical constants with high accuracy and short acquisition times, with the possibility of single shot measurements. Fourier MOKE is thus proposed as a powerful method to perform generalized magneto-optical ellipsometry for a wide range of magnetic materials and devices., This work was supported by UKRI through an EP-SRC studentship, EP/N509668/1 and EP/R513222/1, the European Community under the Horizon 2020 Program, Contract No. 101001290 (3DNANOMAG), the MCIN with funding from European Union NextGenerationEU (PRTR-C17.I1), and the Aragon Government through the Project Q-MAD. Aurelio Hierro-Rodríguez acknowledges the support by Spanish MICIN under grant PID2019-104604RB/AEI/10.13039/501100011033 and by Asturias FICYT under grant AYUD/2021/51185 with the support of FEDER funds. Dédalo Sanz-Hernández acknowledges funding from ANR/CNRS un- der the French "Plan Relance de l’etat" for the preservation of R&D. Luka Skoric acknowledges support from the EPSRC Cambridge NanoDTC EP/L015978/1. Charles N. Christensen acknowledges the UK EPSRC Centre for Doctoral Training in Sensor Technologies for a Healthy and Sustainable Future. Claire Donnelly acknowledges funding from the Max Planck Society Lise Meitner Excellence Program., No