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result(s) for
"Yang, Ji-Hui"
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Van der Waals engineering of magnetism
Pressure-induced changes in the layer stacking order is found to result in new magnetic ground states in two-dimensional insulating CrI3. Such van der Waals engineering should provide ample opportunities to design desired magnetic phases.
Journal Article
Non-Radiative Carrier Recombination Enhanced by Two-Level Process: A First-Principles Study
Non-radiative recombination plays an important role in the performance of optoelectronic semiconductor devices such as solar cells and light-emitting diodes. Most textbook examples assume that the recombination process occurs through a single defect level, where one electron and one hole are captured and recombined. Based on this simple picture, conventional wisdom is that only defect levels near the center of the bandgap can be effective recombination centers. Here, we present a new two-level recombination mechanism: first, one type of carrier is captured through a defect level forming a metastable state; then the local defect configuration rapidly changes to a stable state, where the other type of carrier is captured and recombined through another defect level. This novel mechanism is applied to the recombination center
in CdTe. We show that this two-level process can significantly increase the recombination rate (by three orders of magnitude) in agreement with experiments. We expect that this two-level recombination process can exist in a wide range of semiconductors, so its effect should be carefully examined in characterizing optoelectronic materials.
Journal Article
First-principles studies of charged defect states in intrinsic ferromagnetic semiconductors: the case of monolayer CrI3
Defects play significant roles in spin-current-related physical processes in intrinsic ferromagnetic semiconductors (FMSs), which are great promise for spintronics applications. However, current defect calculation methods cannot be used to investigate charged defects in FMSs due to the spin polarization of both the charged defect states and ionized carriers, which is not well treated in current defect calculation methods. In order to solve this problem, we propose a spin-distinguishable charge correction (SDCC) method that uses spin-polarized band edge charge density instead of spin-unpolarized uniform background charge density as the compensating charge for charged defects. We apply our method to study the defect properties of CrI3 monolayer and find it can be doped n-type under the Cr-rich growth condition but difficult to be doped p-type. The SDCC method proposed here is generally suitable for all FMSs, which will be useful for the studies of defect properties of magnetic semiconductors.
Journal Article
lncRNA028466 regulates Th1/Th2 cytokine expression and associates with Echinococcus granulosus antigen P29 immunity
Background
Cystic echinococcosis (CE) is a parasitic disease that is caused by
Echinococcus granulosus
(Eg)
.
The recombinant
Echinococcus granulosus
antigen P29 (r
Eg
.P29) was shown to confer effective immunity to sheep and mice during
E. granulosus
secondary infection in our previous study. In this study, we sought to investigate the ability of long noncoding RNA 028466 (lncRNA028466) as a regulator for the protective immunity mediated by r
Eg
.P29 vaccination and to study the effects of lncRNA028466 on CD4
+
T cell differentiation in mice spleen.
Methods
Female BALB/c mice were divided into two groups and were vaccinated subcutaneously with r
Eg
.P29 antigen and PBS as a control (12 mice each group). Following prime-boost vaccination, CD4
+
T, CD8
+
T, and B cells from the spleen were isolated by flow cytometry. Quantitative real-time PCR (qRT-PCR) was performed to measure the expression of lncRNA028466 in these three kinds of cells. Then, lncRNA028466 was overexpressed and knocked down in naive CD4
+
T cells, and Th1 and Th2 cytokine expression was detected. qRT-PCR, western blot, and ELISA were performed to evaluate the production of IFN-γ, IL-2, IL-4, and IL-10, and flow cytometry was performed to detect the differentiation of Th1 and Th2 subgroups.
Results
lncRNA028466 was significantly decreased after the second week of immunization with r
Eg
.P29 antigen. The proportion of CD4
+
T cells was increased after r
Eg
.P29 immunization. Overexpression of lncRNA028466 facilitated the production of IL-4, IL-10 and suppressed the production of IFN-γ, IL-2. Furthermore, after transfection with siRNA028466, IL-2 production was facilitated and IL-10 production was suppressed in naive CD4
+
T cells.
Conclusions
Immunization with r
Eg
.P29 downregulated the expression of lncRNA028466, which was related to a higher Th1 immune response and a lower Th2 immune response. Our results suggest that lncRNA028466 may be involved in r
Eg
.P29-mediated immune response by regulating cytokine expression of Th1 and Th2.
Journal Article
Stability and electronic structure of the low- Σ grain boundaries in CdTe: a density functional study
Using first-principles density functional calculations, we investigate the relative stability and electronic structure of the grain boundaries (GBs) in zinc-blende CdTe. Among the low-Σ-value symmetric tilt Σ3 (111), Σ3 (112), Σ5 (120), and Σ5 (130) GBs, we show that the Σ3 (111) GB is always the most stable due to the absence of dangling bonds and wrong bonds. The Σ5 (120) GBs, however, are shown to be more stable than the Σ3 (112) GBs, even though the former has a higher Σ value, and the latter is often used as a model system to study GB effects in zinc-blende semiconductors. Moreover, we find that although containing wrong bonds, the Σ5 (120) GBs are electrically benign due to the short wrong bond lengths, and thus are not as harmful as the Σ3 (112) GBs also having wrong bonds but with longer bond lengths.
Journal Article
Association between gaming disorder and regional homogeneity in highly involved male adult gamers: A pilot resting‐state fMRI study
Background Gaming behavior can induce cerebral changes that may be related to the neurobiological features of gaming disorder (GD). Additionally, individuals with higher levels of depression or impulsivity are more likely to experience GD. Therefore, the present pilot study explored potential neurobiological correlates of GD in the context of depression and impulsivity, after accounting for video gaming behavior. Methods Using resting‐state functional magnetic resonance imaging (fMRI), a cross‐sectional study was conducted with 35 highly involved male adult gamers to examine potential associations between GD severity and regional homogeneity (ReHo) in the entire brain. A mediation model was used to test the role of ReHo in the possible links between depression/impulsivity and GD severity. Results Individuals with greater GD severity showed increased ReHo in the right Heschl's gyrus and decreased ReHo in the right hippocampus (rHip). Furthermore, depression and impulsivity were negatively correlated with ReHo in the rHip, respectively. More importantly, ReHo in the rHip was found to mediate the associations between depression/impulsivity and GD. Conclusions These preliminary findings suggest that GD severity is related to ReHo in brain regions associated with learning/memory/mood and auditory function. Higher levels of depression or impulsivity may potentiate GD through the functional activity of the hippocampus. Our findings advance our understanding of the neurobiological differences behind GD symptoms in highly involved gamers. 35 highly involved male adult gamers participated in this pilot study. Hippocampal dysfunction related to the gaming disorder severity, depression and impulsivity. Hippocampal dysfunction may play a critical role in the development of gaming disorder.
Journal Article
Efficient determination of the Hamiltonian and electronic properties using graph neural network with complete local coordinates
Despite the successes of machine learning methods in physical sciences, the prediction of the Hamiltonian, and thus the electronic properties, is still unsatisfactory. Based on graph neural network (NN) architecture, we present an extendable NN model to determine the Hamiltonian from ab initio data, with only local atomic structures as inputs. The rotational equivariance of the Hamiltonian is achieved by our complete local coordinates (LCs). The LC information, encoded using a convolutional NN and designed to preserve Hermitian symmetry, is used to map hopping parameters onto local structures. We demonstrate the performance of our model using graphene and SiGe random alloys as examples. We show that our NN model, although trained using small-size systems, can predict the Hamiltonian, as well as electronic properties such as band structures and densities of states for large-size systems within the ab initio accuracy, justifying its extensibility. In combination with the high efficiency of our model, which takes only seconds to get the Hamiltonian of a 1728-atom system, the present work provides a general framework to predict electronic properties efficiently and accurately, which provides new insights into computational physics and will accelerate the research for large-scale materials.
Journal Article
Self-regulation of charged defect compensation and formation energy pinning in semiconductors
Current theoretical analyses of defect properties without solving the detailed balance equations often estimate Fermi-level pinning position by omitting free carriers and assume defect concentrations can be always tuned by atomic chemical potentials. This could be misleading in some circumstance. Here we clarify that: (1) Because the Fermi-level pinning is determined not only by defect states but also by free carriers from band-edge states, band-edge states should be treated explicitly in the same footing as the defect states in practice; (2) defect formation energy, thus defect density, could be pinned and independent on atomic chemical potentials due to the entanglement of atomic chemical potentials and Fermi energy, in contrast to the usual expectation that defect formation energy can always be tuned by varying the atomic chemical potentials; and (3) the charged defect compensation behavior, i.e., most of donors are compensated by acceptors or vice versa, is self-regulated when defect formation energies are pinned. The last two phenomena are more dominant in wide-gap semiconductors or when the defect formation energies are small. Using NaCl and CH
3
NH
3
PbI
3
as examples, we illustrate these unexpected behaviors. Our analysis thus provides new insights that enrich the understanding of the defect physics in semiconductors and insulators.
Journal Article
Accelerating the calculation of electron–phonon coupling strength with machine learning
The calculation of electron-phonon couplings (EPCs) is essential for understanding various fundamental physical properties, including electrical transport, optical and superconducting behaviors in materials. However, obtaining EPCs through fully first-principles methods is notably challenging, particularly for large systems or when employing advanced functionals. Here we introduce a machine learning framework to accelerate EPC calculations by utilizing atomic orbital-based Hamiltonian matrices and gradients predicted by an equivariant graph neural network. We demonstrate that our method not only yields EPC values in close agreement with first-principles results but also enhances calculation efficiency by several orders of magnitude. Application to GaAs using the Heyd-Scuseria-Ernzerhof functional reveals the necessity of advanced functionals for accurate carrier mobility predictions, while for the large Kagome crystal CsV
Sb
, our framework reproduces the experimentally observed double domes in pressure-induced superconducting phase diagrams. This machine learning framework offers a powerful and efficient tool for the investigation of diverse EPC-related phenomena in complex materials.
Journal Article