Recent progress in Ti-based nanocomposite anodes for lithium ion batteries

Studying on the anode materials with high energy densities for next-generation lithium-ion batteries (LIBs) is the key for the wide application for electrochemical energy storage devices. Ti-based compounds as promising anode materials are known for their outstanding high-rate capacity and cycling stability as well as improved safety over graphite. However, Ti-based materials still suffer from the low capacity, thus largely limiting their commercialized application. Here, we present an overview of the recent development of Ti-based anode materials in LIBs, and special emphasis is placed on capacity enhancement by rational design of hybrid nanocomposites with conversion-/ alloying-type anodes. This review is expected to provide a guidance for designing novel Ti-based materials for energy storage and conversion. Keywords: lithium-ion batteries (LIBs) anode titania lithium titanateNational Natural Science Foundation (China) (51472137)National Natural Science Foundation (China) (51772163

Catch-Up Distillation: You Only Need to Train Once for Accelerating Sampling

Diffusion Probability Models (DPMs) have made impressive advancements in various machine learning domains. However, achieving high-quality synthetic samples typically involves performing a large number of sampling steps, which impedes the possibility of real-time sample synthesis. Traditional accelerated sampling algorithms via knowledge distillation rely on pre-trained model weights and discrete time step scenarios, necessitating additional training sessions to achieve their goals. To address these issues, we propose the Catch-Up Distillation (CUD), which encourages the current moment output of the velocity estimation model ``catch up'' with its previous moment output. Specifically, CUD adjusts the original Ordinary Differential Equation (ODE) training objective to align the current moment output with both the ground truth label and the previous moment output, utilizing Runge-Kutta-based multi-step alignment distillation for precise ODE estimation while preventing asynchronous updates. Furthermore, we investigate the design space for CUDs under continuous time-step scenarios and analyze how to determine the suitable strategies. To demonstrate CUD's effectiveness, we conduct thorough ablation and comparison experiments on CIFAR-10, MNIST, and ImageNet-64. On CIFAR-10, we obtain a FID of 2.80 by sampling in 15 steps under one-session training and the new state-of-the-art FID of 3.37 by sampling in one step with additional training. This latter result necessitated only 620k iterations with a batch size of 128, in contrast to Consistency Distillation, which demanded 2100k iterations with a larger batch size of 256. Our code is released at https://anonymous.4open.science/r/Catch-Up-Distillation-E31F

Modulation of Excited State Property Based on Benzo[a, c]phenazine Acceptor: Three Typical Excited States and Electroluminescence Performance

Throwing light upon the structure-property relationship of the excited state properties for next-generation fluorescent materials is crucial for the organic light emitting diode (OLED) field. Herein, we designed and synthesized three donor-acceptor (D-A) structure compounds based on a strong spin orbit coupling (SOC) acceptor benzo[a, c]phenazine (DPPZ) to research on the three typical types of excited states, namely, the locally-excited (LE) dominated excited state (CZP-DPPZ), the hybridized local and charge-transfer (HLCT) state (TPA-DPPZ), and the charge-transfer (CT) dominated state with TADF characteristics (PXZ-DPPZ). A theoretical combined experimental research was adopted for the excited state properties and their regulation methods of the three compounds. Benefiting from the HLCT character, TPA-DPPZ achieves the best non-doped device performance with maximum brightness of 61,951 cd m−2 and maximum external quantum efficiency of 3.42%, with both high photoluminescence quantum efficiency of 40.2% and high exciton utilization of 42.8%. Additionally, for the doped OLED, PXZ-DPPZ can achieve a max EQE of 9.35%, due to a suppressed triplet quenching and an enhanced SOC

Target Tracking System Constructed by ELM-AE and Transfer Representation Learning

In the target tracking algorithm, the feature model’s ability to quickly learn image features and the ability to adapt to changes in target features during tracking has always been one of the main research directions of target tracking algorithms. Especially for discriminative target trackers based on image block learning, these two points have become decisive factors affecting the efficiency and robustness of the tracker. However, the performance of most existing similar algorithms on these two abilities cannot achieve satisfactory results. To solve this problem, an efficient and robust feature model is proposed. The feature model first uses extreme learning machine autoencoder (ELM-AE) to quickly perform random feature mapping on complex image features of the target and background image blocks, and then uses the transfer learning ability of transfer representation learning (TRL) to improve the adaptability of random feature space. The feature model is named transfer representation learning with ELM-AE (TRL-ELM-AE). Compared with original complex image features, this model can provide the classifier with more compact and expressive shared features, so that the classifier can learn and classify more quickly and efficiently. In addition, in the target tracking process, the target and background usually change continuously over time. Although the feature migration capability of TRL can already adapt to this, in order to further improve the robustness of the tracker, a strategy of dynamically updating training samples is adopted. Through a large number of experimental and analysis results on the 11 target tracking challenge scenarios proposed by OTB, it is proven that the proposed target tracker has significant advantages over the existing target tracker

Topology Optimization Methods for Flexure Hinge Type Piezoelectric Actuators

Piezoelectric actuators have the obvious advantages of simple and compact structure, high precision and long stroke. However, it is difficult to satisfy the various industrial requirements. Topology optimization method can be used to find the new configurations of the compliant mechanism, and different objective function and constraint conditions can be flexibly used to determine the compliant mechanism. In the research of piezoelectric actuators, due to the advantages of compact structure, no lubrication and large displacement magnification, compliant mechanism is extremely suitable to be introduced into the design of piezoelectric actuators. In recent years, topology optimization method is frequently used to design the compliant mechanism on piezoelectric actuator, and has become a research hotspot. In this chapter, the development of topology optimization method is introduced, the design and research on the compliant mechanism of piezoelectric actuator have been summarized, and the future research direction and challenges of topology optimization design for flexure hinge type piezoelectric actuators are prospected

Lithium titanate hydrates with superfast and stable cycling in lithium ion batteries

Lithium titanate and titanium dioxide are two best-known high-performance electrodes that can cycle around 10,000 times in aprotic lithium ion electrolytes. Here we show there exists more lithium titanate hydrates with superfast and stable cycling. That is, water promotes structural diversity and nanostructuring of compounds, but does not necessarily degrade electrochemical cycling stability or performance in aprotic electrolytes. As a lithium ion battery anode, our multi-phase lithium titanate hydrates show a specific capacity of about 130 mA h g⁻¹ at ∼35 C (fully charged within ∼100 s) and sustain more than 10,000 cycles with capacity fade of only 0.001% per cycle. In situ synchrotron diffraction reveals no 2-phase transformations, but a single solid-solution behavior during battery cycling. So instead of just a nanostructured intermediate to be calcined, lithium titanate hydrates can be the desirable final destination.United States. Department of Energy (Contract DE-AC0206CH11357

Laser in Glaucoma and Ocular Hypertension Trial (LIGHT) in China - A Randomized Controlled Trial: Design and Baseline Characteristics

PURPOSE: To describe the baseline characteristics of a trial to evaluate whether selective laser trabeculoplasty (SLT), as a first-line treatment, provides superior economic and health-related quality of life outcomes to medical treatment in China. DESIGN: The LiGHT China trial is an unmasked, single-center, pragmatic, randomized controlled trial. METHODS: A total of 771 previously undiagnosed patients with primary open angle glaucoma (POAG, 622 patients) or ocular hypertension (OHT, 149 patients) at Zhongshan Ophthalmic Center were recruited from March 2015 to January 2019. Subjects were randomized to SLT-1st (followed by medication then surgery when required) or Medicine-1st (medication followed by surgery when required). The primary outcome was health-related quality of life (HRQL). The secondary outcomes were clinical outcomes, cost, cost-effectiveness, Glaucoma Utility Index, Glaucoma Symptom Scale, visual function, and safety. RESULTS: The mean age of POAG patients was 49.8 years and 38.8 years for OHT. The median intraocular pressure was 20 mm Hg for the 1,105 POAG eyes and 24 mm Hg for the 271 OHT eyes. POAG eyes had thinner central cornea thickness (CCT, 536 µm) than OHT eyes (545 µm). Median mean deviation of the visual field in POAG eyes was -4.2 dB. Median refractive error was -1.5 D for OHT eyes and -1.25 D for POAG eyes. There was no difference between POAG and OHT patients on baseline scores of GUI, GSS and VF-14. The difference between OHT and POAG on the EQ-5D-5L was 0.024. CONCLUSIONS: Compared with participants in the LiGHT UK trial, participants in this trial were younger, more myopic and had more severe visual field defects

Research on the biological mechanism and potential application of CEMIP

Cell migration–inducing protein (CEMIP), also known as KIAA1199 and hyaluronan-binding protein involved in hyaluronan depolymerization, is a new member of the hyaluronidase family that degrades hyaluronic acid (HA) and remodels the extracellular matrix. In recent years, some studies have reported that CEMIP can promote the proliferation, invasion, and adhesion of various tumor cells and can play an important role in bacterial infection and arthritis. This review focuses on the pathological mechanism of CEMIP in a variety of diseases and expounds the function of CEMIP from the aspects of inhibiting cell apoptosis, promoting HA degradation, inducing inflammatory responses and related phosphorylation, adjusting cellular microenvironment, and regulating tissue fibrosis. The diagnosis and treatment strategies targeting CEMIP are also summarized. The various functions of CEMIP show its great potential application value