Discovery and Manipulation of van der Waals Polarons in Sb2O3 Ultrathin Molecular Crystal.

Manipulating single electrons at the atomic scale is vital for mastering complex surface processes governed by the transfer of individual electrons. Polarons, composed of electrons stabilized by electron-phonon coupling, offer a pivotal medium for such manipulation. Here, using scanning tunneling microscopy and spectroscopy (STM/STS) and density functional theory (DFT) calculations, we report the identification and manipulation of a new type of polaron, dubbed van der Waals (vdW) polaron, within mono- to trilayer ultrathin films composed of Sb2O3 molecules that are bonded via vdW attractions. The Sb2O3 films were grown on a graphene-covered SiC(0001) substrate via molecular beam epitaxy. Unlike prior molecular polarons, STM imaging observed polarons at the interstitial sites of the molecular film, presenting unique electronic states and localized band bending. DFT calculations revealed the lowest conduction band as an intermolecular bonding state, capable of ensnaring an extra electron through locally diminished intermolecular distances, thereby forming an intermolecular vdW polaron. We also demonstrated the ability to generate, move, and erase such vdW polarons using an STM tip. Our work uncovers a new type of polaron stabilized by coupling with intermolecular vibrations where vdW interactions dominate, paving the way for designing atomic-scale electron transfer processes and enabling precise tailoring of electron-related properties and functionalities.

Tai Chi increases functional connectivity and decreases chronic fatigue syndrome: A pilot intervention study with machine learning and fMRI analysis.

BACKGROUND: The latest guidance on chronic fatigue syndrome (CFS) recommends exercise therapy. Tai Chi, an exercise method in traditional Chinese medicine, is reportedly helpful for CFS. However, the mechanism remains unclear. The present longitudinal study aimed to detect the influence of Tai Chi on functional brain connectivity in CFS. METHODS: The study recruited 20 CFS patients and 20 healthy controls to receive eight sessions of Tai Chi exercise over a period of one month. Before the Tai Chi exercise, an abnormal functional brain connectivity for recognizing CFS was generated by a linear support vector model. The prediction ability of the structure was validated with a random forest classification under a permutation test. Then, the functional connections (FCs) of the structure were analyzed in the large-scale brain network after Tai Chi exercise while taking the changes in the Fatigue Scale-14, Pittsburgh Sleep Quality Index (PSQI), and the 36-item short-form health survey (SF-36) as clinical effectiveness evaluation. The registration number is ChiCTR2000032577 in the Chinese Clinical Trial Registry. RESULTS: 1) The score of the Fatigue Scale-14 decreased significantly in the CFS patients, and the scores of the PSQI and SF-36 changed significantly both in CFS patients and healthy controls. 2) Sixty FCs were considered significant to discriminate CFS (P = 0.000, best accuracy 90%), with 80.5% ± 9% average accuracy. 3) The FCs that were majorly related to the left frontoparietal network (FPN) and default mode network (DMN) significantly increased (P = 0.0032 and P = 0.001) in CFS patients after Tai Chi exercise. 4) The change of FCs in the left FPN and DMN were positively correlated (r = 0.40, P = 0.012). CONCLUSION: These results demonstrated that the 60 FCs we found using machine learning could be neural biomarkers to discriminate between CFS patients and healthy controls. Tai Chi exercise may improve CFS patients' fatigue syndrome, sleep quality, and body health statement by strengthening the functional connectivity of the left FPN and DMN under these FCs. The findings promote our understanding of Tai Chi exercise's value in treating CFS.

A "Click" Reaction to Engineer MoS2 Field-Effect Transistors with Low Contact Resistance.

Two-dimensional (2D) materials with the atomically thin thickness have attracted great interest in the post-Moore's Law era because of their tremendous potential to continue transistor downscaling and offered advances in device performance at the atomic limit. However, the metal-semiconductor contact is the bottleneck in field-effect transistors (FETs) integrating 2D semiconductors as channel materials. A robust and tunable doping method at the source and drain region of 2D transistors to minimize the contact resistance is highly sought after. Here we report a stable carrier doping method via the mild covalent grafting of maleimides on the surface of 2D transition metal dichalcogenides. The chemisorbed interaction contributes to the efficient carrier doping without degrading the high-performance carrier transport. Density functional theory results further illustrate that the molecular functionalization leads to the mild hybridization and the negligible impact on the conduction bands of monolayer MoS2, avoiding the random scattering from the dopants. Differently from reported molecular treatments, our strategy displays high thermal stability (above 300 °C) and it is compatible with micro/nano processing technology. The contact resistance of MoS2 FETs can be greatly reduced by ∼12 times after molecular functionalization. The Schottky barrier of 44 meV is achieved on monolayer MoS2 FETs, demonstrating efficient charge injection between metal and 2D semiconductor. The mild covalent functionalization of molecules on 2D semiconductors represents a powerful strategy to perform the carrier doping and the device optimization.

Giant anisotropic photonics in the 1D van der Waals semiconductor fibrous red phosphorus.

A confined electronic system can host a wide variety of fascinating electronic, magnetic, valleytronic and photonic phenomena due to its reduced symmetry and quantum confinement effect. For the recently emerging one-dimensional van der Waals (1D vdW) materials with electrons confined in 1D sub-units, an enormous variety of intriguing physical properties and functionalities can be expected. Here, we demonstrate the coexistence of giant linear/nonlinear optical anisotropy and high emission yield in fibrous red phosphorus (FRP), an exotic 1D vdW semiconductor with quasi-flat bands and a sizeable bandgap in the visible spectral range. The degree of photoluminescence (third-order nonlinear) anisotropy can reach 90% (86%), comparable to the best performance achieved so far. Meanwhile, the photoluminescence (third-harmonic generation) intensity in 1D vdW FRP is strong, with quantum efficiency (third-order susceptibility) four (three) times larger than that in the most well-known 2D vdW materials (e.g., MoS2). The concurrent realization of large linear/nonlinear optical anisotropy and emission intensity in 1D vdW FRP paves the way towards transforming the landscape of technological innovations in photonics and optoelectronics.

Adversarial Multi-Path Residual Network for Image Super-Resolution.

Recently, deep convolutional neural networks have demonstrated remarkable progresses on single image super-resolution (SR) problem. However, most of them use more deeper and wider networks to improve SR performance, which is not practical in real-world applications due to large complexity, high computation cost, and low efficiency. In addition, they cannot provide high perception quality and guarantee objective quality simultaneously. To address these limitations, we in this paper propose a novel Adversarial Multipath Residual Network (AMPRN), which can largely suppress the number of network parameters and achieve a higher SR performance compared with the state-of-the-art methods. More specifically, we propose a multi-path residual block (MPRB) for multi-path residual network (MPRN) with fewer network parameters, which can extract abundant local features by fully using features from different paths generated by channel slices. These hierarchical features from all the MPRBs are then jointly aggregated by global gradual feature fusion. Following MPRN, we construct an adversarial gradient network with a gradient loss to make the gradient distribution of the generated SR images and ground truth image closer. In this way, the generated SR images of our model can provide high perception quality and objective quality. Finally, several experimental results demonstrate that our AMPRN achieves better performance in comparison with fewer parameters than the state-of-the-art methods.