Deep learning approach for an interface structure analysis with a large statistical noise in neutron reflectometry

Neutron reflectometry (NR) allows us to probe into the structure of the surfaces and interfaces of various materials such as soft matters and magnetic thin films with a contrast mechanism dependent on isotopic and magnetic states. The neutron beam flux is relatively low compared to that of other sources such as synchrotron radiation; therefore, there has been a strong limitation in the time-resolved measurement and further advanced experiments such as surface imaging. This study aims at the development of a methodology to enable the structural analysis by the NR data with a large statistical error acquired in a short measurement time. The neural network-based method predicts the true NR profile from the data with a 20-fold lower signal compared to that obtained under the conventional measurement condition. This indicates that the acquisition time in the NR measurement can be reduced by more than one order of magnitude. The current method will help achieve remarkable improvement in temporally and spatially resolved NR methods to gain further insight into the surface and interfaces of materials.

Ultrafast Electron Dynamics in Magnetic Thin Films

In past decades, ultrafast spin dynamics in magnetic systems have been associated with heat deposition from high energy laser pulses, limiting the selective access to spin order. Here, we use a long wavelength terahertz (THz) pump–optical probe setup to measure structural features in the ultrafast time scale. We find that complete demagnetization is possible with <6 THz pulses. This occurs concurrently with longitudinal acoustic phonons and an electronic response.

Microfluidic Synthesis, Control, and Sensing of Magnetic Nanoparticles: A Review

Magnetic nanoparticles have attracted significant attention in various disciplines, including engineering and medicine. Microfluidic chips and lab-on-a-chip devices, with precise control over small volumes of fluids and tiny particles, are appropriate tools for the synthesis, manipulation, and evaluation of nanoparticles. Moreover, the controllability and automation offered by the microfluidic chips in combination with the unique capabilities of the magnetic nanoparticles and their ability to be remotely controlled and detected, have recently provided tremendous advances in biotechnology. In particular, microfluidic chips with magnetic nanoparticles serve as sensitive, high throughput, and portable devices for contactless detecting and manipulating DNAs, RNAs, living cells, and viruses. In this work, we review recent fundamental advances in the field with a focus on biomedical applications. First, we study novel microfluidic-based methods in synthesizing magnetic nanoparticles as well as microparticles encapsulating them. We review both continues-flow and droplet-based microreactors, including the ones based on the cross-flow, co-flow, and flow-focusing methods. Then, we investigate the microfluidic-based methods for manipulating tiny magnetic particles. These manipulation techniques include the ones based on external magnets, embedded micro-coils, and magnetic thin films. Finally, we review techniques invented for the detection and magnetic measurement of magnetic nanoparticles and magnetically labeled bioparticles. We include the advances in anisotropic magnetoresistive, giant magnetoresistive, tunneling magnetoresistive, and magnetorelaxometry sensors. Overall, this review covers a wide range of the field uniquely and provides essential information for designing “lab-on-a-chip” systems for synthesizing magnetic nanoparticles, labeling bioparticles with them, and sorting and detecting them on a single chip.