Catálogo de publicaciones - revistas

<jats:p>We demonstrate that radio frequency (RF) magnetron sputtering technique can modify the perpendicular magnetic anisotropy (PMA) of Pt/Co/normal metal (NM) thin films. Influence of ion irradiation during RF magnetron sputtering should not be neglected and it can weaken PMA of the deposited magnetic films. The magnitude of this influence can be controlled by tuning RF magnetron sputtering deposition conditions and the upper NM layer thickness. According to the stopping and range of ions in matter (SRIM) simulation results, defects such as displacement atoms and vacancies in the deposited film will increase after the RF magnetron sputtering, which can account for the weakness of PMA. The amplitude changes of the Hall resistance and the threshold current intensity of spin orbit torque (SOT) induced magnetization switching also can be modified. Our study could be useful for controlling magnetic properties of PMA films and designing new type of SOT-based spintronic devices.</jats:p>

<jats:p>In recent years, low-dimensional materials have received extensive attention in the field of electronics and optoelectronics. Among them, photoelectric devices based on photoconductive effect in low-dimensional materials have a broad development space. In contrast to positive photoconductivity, negative photoconductivity (NPC) refers to a phenomenon that the conductivity decreases under illumination. It has novel application prospects in the field of optoelectronics, memory, and gas detection, <jats:italic>etc</jats:italic>. In this paper, we review reports about the NPC effect in low-dimensional materials and systematically summarize the mechanisms to form the NPC effect in existing low-dimensional materials.</jats:p>

<jats:p>We review the experimental and computational data about the propagation of neural signals in myelinated axons in mice, cats, rabbits, and frogs published in the past five decades. In contrast to the natural assumption that neural signals occur one by one in time and in space, we figure out that neural signals are highly overlapped in time between neighboring nodes. This phenomenon was occasionally illustrated in some early reports, but seemed to have been overlooked for some time. The shift in time between two successive neural signals from neighboring nodes, defined as relay time <jats:italic>τ</jats:italic>, was calculated to be only 16.3 μs–87.0 μs, <jats:italic>i.e.</jats:italic>, 0.8 %–4.4 % of the average duration of an action potential peak (roughly 2 ms). We present a clearer picture of the exact physical process about how the information transmits along a myelinated axon, rather than a whole action potential peak, what is transmitted is only a rising electric field caused by transmembrane ion flows. Here in the paper, <jats:italic>τ</jats:italic> represents the waiting time until the neighboring node senses an attenuated electric field reaching the threshold to trigger the open state. The mechanisms addressed in this work have the potential to be universal, and may hold clues to revealing the exact triggering processes of voltage-gated ion channels and various brain functions.</jats:p>

<jats:p>A new method of generating and detecting terahertz waves is proposed. Low-temperature-grown gallium arsenide (LT-GaAs) thin films are prepared by etching a sacrificial layer (AlAs) in a four-layer epitaxial structure constituted with LT-GaAs, AlAs, GaAs, and semi-insulating gallium arsenide (SI-GaAs). The thin films are then transferred to clean silicon for fabricating the LT-GaAs thin film antennas. The quality and transmission characteristics of the films are analyzed by an 800-nm asynchronous ultrafast time domain spectroscopy system, and the degree of bonding between the film and silicon wafer is determined. Two LT-GaAs thin film antennas for generating and detecting the terahertz waves are tested with a 1550-nm femtosecond laser. The terahertz signal is successfully detected, proving the feasibility of this home-made LT-GaAs photoconductive antennas. This work lays a foundation for studying the mechanism of terahertz wave generation in GaAs photoconductive antennas below the semiconductor band gap.</jats:p>

<jats:p>Dual phase grating x-ray interferometry is compatible with common imaging detectors, and abandons the use of an absorption analyzer grating to reduce the radiation dose. When using x-ray tubes, an absorbing source grating must be introduced into the dual phase grating interferometer. In order to attain a high fringe visibility, in this work we conduct a quantitative coherence analysis of dual phase grating interferometry to find how the source grating affects the fringe visibility. Theoretical analysis shows that with the generalized Lau condition satisfied, the fringe visibility is influenced by the duty cycle of the source grating and the transmission through the grating bar. And the influence of the source grating profile on the fringe visibility is independent of the phase grating type. Numerical results illustrate that the maximum achievable fringe visibility decreases significantly with increasing transmission in the grating bar. Under a given transmission, one can always find an optimal duty cycle to maximize the fringe visibility. These results can be used as general guidelines for designing and optimizing dual phase grating x-ray interferometers for potential applications.</jats:p>

<jats:p>It is generally believed that, in ghost imaging, there has to be a compromise between resolution and visibility. Here we propose and demonstrate an iterative filtered ghost imaging scheme whereby a super-resolution image of a grayscale object is achieved, while at the same time the signal-to-noise ratio (SNR) and visibility are greatly improved, without adding complexity. The dependence of the SNR, visibility, and resolution on the number of iterations is also investigated and discussed. Moreover, with the use of compressed sensing the sampling number can be reduced to less than 1% of the Nyquist limit, while maintaining image quality with a resolution that can exceed the Rayleigh diffraction bound by more than a factor of 10.</jats:p>

<jats:p>The folding of many small proteins is kinetically a two-state process with one major free-energy barrier to overcome, which can be roughly regarded as the inverse process of unfolding. In this work, we first use a Gaussian network model to predict the folding nucleus corresponding to the major free-energy barrier of protein 2GB1, and find that the folding nucleus is located in the <jats:italic>β</jats:italic>-sheet domain. High-temperature molecular dynamics simulations are then used to investigate the unfolding process of 2GB1. We draw free-energy surface from unfolding simulations, taking RMSD and contact number as reaction coordinates, which confirms that the folding of 2GB1 is kinetically a two-state process. The comparison of the contact maps before and after the free energy barrier indicates that the transition from native to non-native structure of the protein is kinetically caused by the destruction of the <jats:italic>β</jats:italic>-sheet domain, which manifests that the folding nucleus is indeed located in the <jats:italic>β</jats:italic>-sheet domain. Moreover, the constrained MD simulation further confirms that the destruction of the secondary structures does not alter the topology of the protein retained by the folding nucleus. These results provide vital information for upcoming researchers to further understand protein folding in similar systems.</jats:p>

<jats:p>In high intensity focused ultrasound (HIFU) treatment, it is crucial to accurately identify denatured and normal biological tissues. In this paper, a novel method based on compressed sensing (CS) and refined composite multi-scale fuzzy entropy (RCMFE) is proposed. First, CS is used to denoise the HIFU echo signals. Then the multi-scale fuzzy entropy (MFE) and RCMFE of the denoised HIFU echo signals are calculated. This study analyzed 90 cases of HIFU echo signals, including 45 cases in normal status and 45 cases in denatured status, and the results show that although both MFE and RCMFE can be used to identify denatured tissues, the intra-class distance of RCMFE on each scale factor is smaller than MFE, and the inter-class distance is larger than MFE. Compared with MFE, RCMFE can calculate the complexity of the signal more accurately and improve the stability, compactness, and separability. When RCMFE is selected as the characteristic parameter, the RCMFE difference between denatured and normal biological tissues is more evident than that of MFE, which helps doctors evaluate the treatment effect more accurately. When the scale factor is selected as 16, the best distinguishing effect can be obtained.</jats:p>

<jats:p>Structure evaluation is critical to <jats:italic>in silico</jats:italic> 3-dimensional structure predictions for biomacromolecules such as proteins and RNAs. For proteins, structure evaluation has been paid attention over three decades along with protein folding problem, and statistical potentials have been shown to be effective and efficient in protein structure prediction and evaluation. In recent two decades, RNA folding problem has attracted much attention and several statistical potentials have been developed for RNA structure evaluation, partially with the aid of the progress in protein structure prediction. In this review, we will firstly give a brief overview on the existing statistical potentials for protein structure evaluation. Afterwards, we will introduce the recently developed statistical potentials for RNA structure evaluation. Finally, we will emphasize the perspective on developing new statistical potentials for RNAs in the near future.</jats:p>

<jats:p>Many numerical methods, such as tensor network approaches including density matrix renormalization group calculations, have been developed to calculate the extreme/ground states of quantum many-body systems. However, little attention has been paid to the central states, which are exponentially close to each other in terms of system size. We propose a delta-Davidson (DELDAV) method to efficiently find such interior (including the central) states in many-spin systems. The DELDAV method utilizes a delta filter in Chebyshev polynomial expansion combined with subspace diagonalization to overcome the nearly degenerate problem. Numerical experiments on Ising spin chain and spin glass shards show the correctness, efficiency, and robustness of the proposed method in finding the interior states as well as the ground states. The sought interior states may be employed to identify many-body localization phase, quantum chaos, and extremely long-time dynamical structure.</jats:p>