Nankai University

About: Nankai University is a education organization based out in Tianjin, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 42964 authors who have published 51866 publications receiving 1127896 citations. The organization is also known as: Nánkāi Dàxué.

Mitophagy receptor FUNDC1 regulates mitochondrial dynamics and mitophagy.

Abstract: Mitochondrial fragmentation due to imbalanced fission and fusion of mitochondria is a prerequisite for mitophagy, however, the exact “coupling” of mitochondrial dynamics and mitophagy remains unclear. We have previously identified that FUNDC1 recruits MAP1LC3B/LC3B (LC3) through its LC3-interacting region (LIR) motif to initiate mitophagy in mammalian cells. Here, we show that FUNDC1 interacts with both DNM1L/DRP1 and OPA1 to coordinate mitochondrial fission or fusion and mitophagy. OPA1 interacted with FUNDC1 via its Lys70 (K70) residue, and mutation of K70 to Ala (A), but not to Arg (R), abolished the interaction and promoted mitochondrial fission and mitophagy. Mitochondrial stress such as selenite or FCCP treatment caused the disassembly of the FUNDC1-OPA1 complex while enhancing DNM1L recruitment to the mitochondria. Furthermore, we observed that dephosphorylation of FUNDC1 under stress conditions promotes the dissociation of FUNDC1 from OPA1 and association with DNM1L. Our data suggest that ...

Fast Sodium Storage in TiO2@CNT@C Nanorods for High‐Performance Na‐Ion Capacitors

Abstract: Na-ion capacitors have attracted extensive interest due to the combination of the merits of high energy density of batteries and high power density as well as long cycle life of capacitors. Here, a novel Na-ion capacitor, utilizing TiO2@CNT@C nanorods as an intercalation-type anode and biomass-derived carbon with high surface area as an ion adsorption cathode in an organic electrolyte, is reported. The advanced architecture of TiO2@CNT@C nanorods, prepared by electrospinning method, demonstrates excellent cyclic stability and outstanding rate capability in half cells. The contribution of extrinsic pseudocapacitance affects the rate capability to a large extent, which is identified by kinetics analysis. A key finding is that ion/electron transfer dynamics of TiO2@CNT@C could be effectively enhanced due to the addition of multiwalled carbon nanotubes. Also, the biomass-derived carbon with high surface area displays high specific capacity and excellent rate capability. Owing to the merits of structures and excellent performances of both anode and cathode materials, the assembled Na-ion capacitors provide an exceptionally high energy density (81.2 W h kg−1) and high power density (12 400 W kg−1) within 1.0–4.0 V. Meanwhile, the Na-ion capacitors achieve 85.3% capacity retention after 5000 cycles tested at 1 A g−1.

Magnesium nanowires: enhanced kinetics for hydrogen absorption and desorption.

Abstract: Mg nanowires with the diameters of 30−50 nm, 80−100 nm, and 150−170 nm, which were prepared via a vapor-transport method, exhibited enhanced kinetics for hydrogen absorption/desorption. The present results clearly show that thinner Mg/MgH2 nanowires have a much lower desorption energy than that of thicker nanowires or bulk Mg/MgH2, indicating that changes in kinetics and thermodynamics are expected if the diameters of the nanowires are thinner than 30 nm.

Crowd Counting with Deep Negative Correlation Learning

Abstract: Deep convolutional networks (ConvNets) have achieved unprecedented performances on many computer vision tasks. However, their adaptations to crowd counting on single images are still in their infancy and suffer from severe over-fitting. Here we propose a new learning strategy to produce generalizable features by way of deep negative correlation learning (NCL). More specifically, we deeply learn a pool of decorrelated regressors with sound generalization capabilities through managing their intrinsic diversities. Our proposed method, named decorrelated ConvNet (D-ConvNet), is end-to-end-trainable and independent of the backbone fully-convolutional network architectures. Extensive experiments on very deep VGGNet as well as our customized network structure indicate the superiority of D-ConvNet when compared with several state-of-the-art methods. Our implementation will be released at https://github.com/shizenglin/Deep-NCL

Bioinspired Ultrasensitive and Stretchable MXene-Based Strain Sensor via Nacre-Mimetic Microscale "Brick-and-Mortar" Architecture.

Abstract: The development of wearable strain sensors with simultaneous large stretchability (strain >55%) and high sensitivity (gauge factor >100) remains a grand challenge to this day. Drawing on inspiration from nature, nacre has demonstrated outstanding mechanical properties, especially combining high strength and toughness, which is due in part to its delicate hierarchical layered architecture with rich interfacial interactions. We demonstrate that strain sensors based on this nacre-mimetic microscale “brick-and-mortar” architecture can simultaneously achieve ultrahigh sensitivity and large stretchability while performing well in linearity, reliability, long-term durability, and monotonicity. The bioinspired sensor demonstrated a gauge factor >200 over a range of working strains up to 83% and achieved a high gauge factor exceeding 8700 in the strain region of 76–83%. This successful combination of high sensitivity and large stretchability is attributed to (1) the microscale hierarchical architecture derived fro...