Zinc-ion batteries are under current research focus because of their uniqueness in low cost and high safety. However, it is still desirable to improve the rate performance by improving the Zn (de)intercalation kinetics and long-cycle stability by eliminating the dendrite formation problem. Herein, the first paradigm of a high-rate and ultrastable flexible quasi-solid-state zinc-ion battery is constructed from a novel 2D ultrathin layered zinc orthovanadate array cathode, a Zn array anode supported by a conductive porous graphene foam, and a gel electrolyte. The nanoarray structure for both electrodes assures the high rate capability and alleviates the dendrite growth. The flexible Zn-ion battery has a depth of discharge of ≈100% for the cathode and 66% for the anode, and delivers an impressive high-rate of 50 C (discharge in 60 s), long-term durability of 2000 cycles at 20 C, and unprecedented energy density ≈115 Wh kg , together with a peak power density ≈5.1 kW kg (calculation includes masses of cathode, anode, and current collectors). First principles calculations and quantitative kinetics analysis show that the high-rate and stable properties are correlated with the 2D fast ion-migration pathways and the introduced intercalation pseudocapacitance.

We report effective and stable electron doping of monolayer molybdenum disulfide (MoS2) by cesium carbonate (Cs2CO3) surface functionalization. The electron charge carrier concentration in exfoliated monolayer MoS2 can be increased by about 9 times after Cs2CO3 functionalization. The n-type doping effect was evaluated by in situ transport measurements of MoS2 field-effect transistors (FETs) and further corroborated by in situ ultraviolet photoelectron spectroscopy, X-ray photoelectron spectroscopy, and Raman scattering measurements. The electron doping enhances the formation of negative trions (i.e., a quasiparticle comprising two electrons and one hole) in monolayer MoS2 under light irradiation and significantly reduces the charge recombination of photoexcited electron-hole pairs. This results in large photoluminescence suppression and an obvious photocurrent enhancement in monolayer MoS2 FETs.

For millimeter wave (mmWave) massive multipleinput multiple-output (MIMO) systems, hybrid processing architecture is usually used to reduce the complexity and cost, which poses a very challenging issue in channel estimation. In this paper, deep convolutional neural network (CNN) is employed to address this problem. We first propose a spatialfrequency CNN (SF-CNN) based channel estimation exploiting both the spatial and frequency correlation, where the corrupted channel matrices at adjacent subcarriers are input into the CNN simultaneously. Then, exploiting the temporal correlation in timevarying channels, a spatial-frequency-temporal CNN (SFT-CNN) based approach is developed to further improve the accuracy. Moreover, we design a spatial pilot-reduced CNN (SPR-CNN) to save spatial pilot overhead for channel estimation, where channels in several successive coherence intervals are grouped and estimated by a channel estimation unit with memory. Numerical results show that the proposed SF-CNN and SFT-CNN based approaches outperform the non-ideal minimum meansquared error (MMSE) estimator but with reduced complexity, and achieve the performance close to the ideal MMSE estimator that is impossible to be implemented in practical situations. They are also robust to different propagation scenarios. The SPR-CNN based approach achieves comparable performance to SF-CNN based approach while only requires about one third of spatial pilot overhead at the cost of slightly increased complexity. Our work clearly shows that deep CNN can efficiently exploit channel correlation to improve the estimation performance for mmWave massive MIMO systems.

Identifying cancer cells and quantifying cancer-related events in particular organelles in a rapid and sensitive fashion are important for early diagnosis and for studies on pathology and therapeutics of cancers. Herein a smart "off-on" cyclooxygenase-2-specific fluorescence probe (ANQ-IMC-6), able to report the presence of cancer cells and to image Golgi-related events, has been designed and evaluated. Cyclooxygenase-2 (COX-2) has been used as imaging target in the probe design, since this enzyme is a biomarker of virtually all cancer cell lines. In the free state in aqueous solution, ANQ-IMC-6 mainly exists in a folded conformation where probe fluorescence is quenched through photoinduced electron transfer between the fluorophore acenaphtho[1,2-b]quinoxaline (ANQ) and the recognition group, indomethacin (IMC). Fluorescence is turned on, by restraining the photoinduced electron transfer, when ANQ-IMC-6 is forced to adopt the unfolded state following binding to COX-2 in the Golgi apparatus of cancer cells. ANQ-IMC-6 provides high signal-to-background staining and has been successfully used to rapidly differentiate cancer cells from normal cells when using flow cytometry and one- and two-photon fluorescence microscopic imaging. Furthermore, ANQ-IMC-6 may be able to visualize dynamic changes of the Golgi apparatus during cancer cell apoptosis, with possible application to early diagnosis.