Improving the stability of amorphous silicon solar cells by chemical annealing

Amorphous silicon solar cells have been extensively studied. However, it is found that the properties of a-Si:H solar cells degrade upon light illumination, and this limits their application. Recently, it has been shown that this instability is correlated with the presence of SiH2 bonds, and a technique, namely chemical annealing, was suggested to improve the stability of a-Si:H. Although a number of results have been reported, no chemical annealed devices with good quality were reported;In this work, chemical annealing technique was studied to improve the stability of a-Si:H solar cells. It is found that when the annealing was done in hydrogen plasma, the films remained amorphous; in contrast, when in helium plasma, and the annealing time is equal or more than 20 seconds, the films became crystalline. These unusual results show that it is not necessary to have a high hydrogen dilution to obtain nanocrystalline films, and contradict the generally accepted assumption that high hydrogen dilutions are needed to crystallize the amorphous films based on the reactive etching of H ions. Instead, it might be the case that not only the reactive etching effect from the H ions, but also the ion bombardment play a role in crystallizing the amorphous films

Investigation of the phase formation and magnetic properties of the Fe-N thin films deposited by reactive pulsed laser deposition

Fe-N films have been grown on SiO2/Si(100) substrates by reactive pulsed laser deposition (PLD). Series of films were deposited at 200C and at 2500C, with a wide range of nitrogen pressures. Nitrogen pressure was found to affect film average composition, structure, phase percentages, and magnetic properties of the films. Deposition temperature also affected the nitrogen content, structure, phase percentages and magnetic properties of the films. The saturation magnetization of the films is shown to depend not only on their average nitrogen content but also on the phases and their relative amounts that make up the films. In particular, the iron nitrides [Gamma\u27]-Fe4N, and [Epsilon]-Fe3N (which has a wide range of composition) play a major role in determining the magnetization. Results can be understood in terms of the relative contributions of deposition rate and atomic surface diffusion in producing thin-film structure. To date, no giant moments larger than M[Subscript s] of pure Fe have been observed in this investigation. Subsequently annealing at 2000C shows that for the sample deposited at 10m Torr and 200C the perpendicular magnetic anisotropy is suppressed after annealing. This can be understood by the explanation that the annealing process releases the stress. For the sample deposited at 40mTorr and 200C (which is amorphous or possibly nanocrystalline), after annealing its magnetization is found to decrease significantly. This may be due to the reason that annealing makes the distribution of the introduced nitrogen atoms more homogeneous (or ordered). N nearest neighbors are proposed to tend to decrease the moments on Fe atoms, and thus it is assumed that spreading the N more homogeneously could cause more iron atoms to have N neighbors and thus overall moment to decrease

High-performance cVEP-BCI under minimal calibration

The ultimate goal of brain-computer interfaces (BCIs) based on visual modulation paradigms is to achieve high-speed performance without the burden of extensive calibration. Code-modulated visual evoked potential-based BCIs (cVEP-BCIs) modulated by broadband white noise (WN) offer various advantages, including increased communication speed, expanded encoding target capabilities, and enhanced coding flexibility. However, the complexity of the spatial-temporal patterns under broadband stimuli necessitates extensive calibration for effective target identification in cVEP-BCIs. Consequently, the information transfer rate (ITR) of cVEP-BCI under limited calibration usually stays around 100 bits per minute (bpm), significantly lagging behind state-of-the-art steady-state visual evoked potential-based BCIs (SSVEP-BCIs), which achieve rates above 200 bpm. To enhance the performance of cVEP-BCIs with minimal calibration, we devised an efficient calibration stage involving a brief single-target flickering, lasting less than a minute, to extract generalizable spatial-temporal patterns. Leveraging the calibration data, we developed two complementary methods to construct cVEP temporal patterns: the linear modeling method based on the stimulus sequence and the transfer learning techniques using cross-subject data. As a result, we achieved the highest ITR of 250 bpm under a minute of calibration, which has been shown to be comparable to the state-of-the-art SSVEP paradigms. In summary, our work significantly improved the cVEP performance under few-shot learning, which is expected to expand the practicality and usability of cVEP-BCIs.Comment: 35 pages, 5 figure

From confined spinons to emergent fermions: Observation of elementary magnetic excitations in a transverse-field Ising chain

We report on spectroscopy study of elementary magnetic excitations in an Ising-like antiferromagnetic chain compound SrCo$_2$V$_2$O$_8$ as a function of temperature and applied transverse magnetic field up to 25 T. An optical as well as an acoustic branch of confined spinons, the elementary excitations at zero field, are identified in the antiferromagnetic phase below the N\'{e}el temperature of 5 K and described by a one-dimensional Schr\"{o}dinger equation. The confinement can be suppressed by an applied transverse field and a quantum disordered phase is induced at 7 T. In this disordered paramagnetic phase, we observe three emergent fermionic excitations with different transverse-field dependencies. The nature of these modes is clarified by studying spin dynamic structure factor of a 1D transverse-field Heisenberg-Ising (XXZ) model using the method of infinite time evolving block decimation. Our work reveals emergent quantum phenomena and provides a concrete system for testifying theoretical predications of one-dimension quantum spin models.Comment: 8 pages and 6 figure

Highly anisotropic transient optical response of charge density wave order in ZrTe3_3

Low dimensionality in CDW systems leads to anisotropic optical properties, in both equilibrium and non-equilibrium conditions. Here we perform polarized two-color pump probe measurements on a quasi-1D material ZrTe$_3$, in order to study the anisotropic transient optical response in the CDW state. Profound in-plane anisotropy is observed with respect to polarization of probe photons. Below $T_\mathrm{CDW}$ both the quasi-particle relaxation signal and amplitude mode (AM) oscillation signal are much larger with $\mathbf{E}_\mathrm{pr}$ nearly parallel to $a$ axis ($\mathbf{E}_\mathrm{pr} \parallel a$) than for $\mathbf{E}_\mathrm{pr}$ parallel to $b$ axis ($\mathbf{E}_\mathrm{pr} \parallel b$). This reveals that $\mathbf{E}_\mathrm{pr} \parallel a$ signal is much more sensitive to the variation of the CDW gap. Interestingly, the lifetime of the AM oscillations observed with $\mathbf{E}_\mathrm{pr} \parallel b$ is longer than $\mathbf{E}_\mathrm{pr} \parallel a$. Moreover, at high pump fluence where the electronic order melts and the AM oscillations vanish for $\mathbf{E}_\mathrm{pr} \parallel a$ , the AM oscillatory response still persists for $\mathbf{E}_\mathrm{pr} \parallel b$. We discuss possible origins that lead to such unusual discrepancy between the two polarizations.Comment: 6 pages, 4 figure

Concept Drift Detection by Tracking Weighted Prediction Confidence of Incremental Learning

Data stream mining is great significant in many real-world scenarios, especially in the big data area. However, conventional machine learning algorithms are incapable to process because of its two characteristics (1) potential unlimited number of data is generated in real-time way, it is impossible to store all the data (2) evolving over time, namely, concept drift, will influence the performance of predictor trained on previous data. Concept drift detection method could detect and locate the concept drift in data stream. However, existing methods only utilize the prediction result as indicator. In this article, we propose a weighted concept drift indicator based on incremental ensemble learning to detect the concept. The indicator not only considers the prediction result, but the change of prediction stability of predictor with occurs of concept drift. Also, an incremental ensemble learning based on vote mechanism is especially used to get constantly updated value of indicator. Based on the experiment result on both benchmark and real-world dataset, our method could effectively detect concept drift and outperform other existing methods

Superconductivity in the vicinity of antiferromagnetic order in CrAs

One of the common features of unconventional, magnetically mediated superconductivity as found in the heavy-fermions, high-transition-temperature (high-Tc) cuprates, and iron pnictides superconductors is that the superconductivity emerges in the vicinity of long-range antiferromagnetically ordered state.[1] In addition to doping charge carriers, the application of external physical pressure has been taken as an effective and clean approach to induce the unconventional superconductivity near a magnetic quantum critical point (QCP).[2,3] Superconductivity has been observed in a majority of 3d transition-metal compounds,[4-9] except for the Cr- and Mn-based compounds in the sense that the low-lying states near Fermi level are dominated by their 3d electrons. Herein, we report on the discovery of superconductivity on the verge of antiferromagnetic order in CrAs via the application of external high pressure. Bulk superconductivity with Tc ~ 2 K emerges at the critical pressure Pc ~ 8 kbar, where the first-order antiferromagnetic transition at TN = 265 K under ambient pressure is completely suppressed. Abnormal normal-state properties associated with a magnetic QCP have been observed nearby Pc. The close proximity of superconductivity to an antiferromagnetic order suggests an unconventional pairing mechanism for the superconducting state of CrAs. The present finding opens a new avenue for searching novel superconductors in the Cr and other transitional-metal based systems

Comparative study on the thermoelectric effect of parent oxypnictides LaTTAsO (TT = Fe, Ni)

The thermopower and Nernst effect were investigated for undoped parent compounds LaFeAsO and LaNiAsO. Both thermopower and Nernst signal in iron-based LaFeAsO are significantly larger than those in nickel-based LaNiAsO. Furthermore, abrupt changes in both thermopower and Nernst effect are observed below the structural phase transition temperature and spin-density wave (SDW) type antiferromagnetic (AFM) order temperature in Fe-based LaFeAsO. On the other hand, Nernst effect is very small in the Ni-based LaNiAsO and it is weakly temperature-dependent, reminiscent of the case in normal metals. We suggest that the effect of SDW order on the spin scattering rate should play an important role in the anomalous temperature dependence of Hall effect and Nernst effect in LaFeAsO. The contrast behavior between the LaFeAsO and LaNiAsO systems implies that the LaFeAsO system is fundamentally different from the LaNiAsO system and this may provide clues to the mechanism of high $T_c$ superconductivity in the Fe-based systems.Comment: 6 pages, 6 figure