Failure mechanisms of the Li(Ni0.6Co0.2Mn0.2)O2-Li4Ti5O12 lithium-ion batteries in long-time high-rate cycle.

With the ever-growing widespread use of lithium-ion batteries in heavy machinery and daily life, the demand for improved longevity and high-rate performance is escalating. While Li4Ti5O12 (LTO) batteries excel in safety and cycling performance, their full potential for long-term, high-rate cycling still yet remains unrealized. In this paper, we present an analysis of a pouch battery with an LTO anode system that was cycled for an extended period at high rates. We compared the performance changes and internal component properties between fresh and cycled batteries. Our results reveal that, after tens of thousands of high-rate cycles, microcracks emerged on the cathode electrode material (NCM622) particles of the battery, whereas the LTO remained largely unchanged. Additionally, we observed significant electrolyte reduction, characterized the separator surface, and measured its properties. Our findings indicate that the electrolyte reactions are the primary cause of battery failure, leading to capacity fading and impedance increase. This research provides valuable insights into the failure mechanisms of lithium-ion batteries at high rates, thus contributing to the improvement of high-rate lithium-ion batteries.

COVID-19 vaccine hesitancy and influencing factors among Chinese hospital staff: a cross-sectional study.

We aimed to investigate the willingness of hospital staff to receive the COVID-19 vaccine and explore the associated factors and reasons of vaccine hesitancy among Chinese hospital staff, which were not yet known. A cross-sectional questionnaire survey was conducted online on the vaccine hesitancy of staff in a grade A tertiary general hospital in Beijing from February 22 to 23, 2023. Univariate and multivariate logistic regression were used to assess associations between potential influencing factors and vaccine hesitancy. A total of 3269 valid respondents were included, and the rate of COVID-19 vaccine hesitancy was 32.67%. Multivariate logistic regression showed that women [1.50 (1.22-1.83)], having high-school education level [1.69 (1.04-2.76)], college degree [2.24 (1.35-3.72)] or graduate degree [2.31 (1.33-4.03)], and having underlying disease [1.41 (1.12-1.77)] were associated with a higher rate of COVID-19 vaccine hesitancy. The main reasons for vaccine hesitancy included doubts for the safety and effectiveness of COVID-19 vaccine and worries in adverse reactions. Hospital staff's willingness to vaccinate COVID-19 vaccine is generally high in the study. Hospitals should spread the knowledge of COVID-19 vaccine through multiple channels to improve the cognition of hospital staff and encourage vaccination based on associated factors.

Lower Limb Joint Torque Prediction Using Long Short-Term Memory Network and Gaussian Process Regression.

The accurate prediction of joint torque is required in various applications. Some traditional methods, such as the inverse dynamics model and the electromyography (EMG)-driven neuromusculoskeletal (NMS) model, depend on ground reaction force (GRF) measurements and involve complex optimization solution processes, respectively. Recently, machine learning methods have been popularly used to predict joint torque with surface electromyography (sEMG) signals and kinematic information as inputs. This study aims to predict lower limb joint torque in the sagittal plane during walking, using a long short-term memory (LSTM) model and Gaussian process regression (GPR) model, respectively, with seven characteristics extracted from the sEMG signals of five muscles and three joint angles as inputs. The majority of the normalized root mean squared error (NRMSE) values in both models are below 15%, most Pearson correlation coefficient (R) values exceed 0.85, and most decisive factor (R2) values surpass 0.75. These results indicate that the joint prediction of torque is feasible using machine learning methods with sEMG signals and joint angles as inputs.

Facile synthesis of carbon and oxygen vacancy co-modified TiNb6O17 as an anode material for lithium-ion batteries.

Titanium niobium oxides (TNOs), benefitting from their large specific capacity and Wadsley-Roth shear structure, are competitive anode materials for high-energy density and high-rate lithium-ion batteries. Herein, carbon and oxygen vacancy co-modified TiNb6O17 (A-TNO) was synthesized through a facile sol-gel reaction with subsequent heat treatment and ball-milling. Characterizations indicated that A-TNO is composed of nanosized primary particles, and the carbon content is about 0.7 wt%. The nanoparticles increase the contact area of the electrode and electrolyte and shorten the lithium-ion diffusion distance. The carbon and oxygen vacancies decrease the charge transfer resistance and enhance the Li-ion diffusion coefficient of the obtained anode material. As a result of these advantages, A-TNO exhibits excellent rate performance (208 and 177 mA h g-1 at 10C and 20C, respectively). This work reveals that A-TNO possesses good electrochemical performance and has a facile preparation process, thus A-TNO is believed to be a potential anode material for large-scale applications.

TiO2(B) nanosheets modified Li4Ti5O12microsphere anode for high-rate lithium-ion batteries.

With the increasing applications of Lithium-ion batteries in heavy equipment and engineering machinery, the requirements of rate capability are continuously growing. The high-rate performance of Li4Ti5O12(LTO) needs to be further improved. In this paper, we synthesized LTO microsphere-TiO2(B) nanosheets (LTO-TOB) composite by using a solvothermal method and subsequent calcination. LTO-TOB composite combines the merits of TiO2(B) and LTO, resulting in excellent high-rate capability (144.8, 139.3 and 124.4 mAh g-1at 20 C, 30 C and 50 C) and superior cycling stability (98.9% capability retention after 500 cycles at 5 C). Its excellent electrochemical properties root in the large surface area, high grain-boundary density and pseudocapacitive effect of LTO-TOB. This work reveals that LTO-TOB composite can be a potential anode for high power and energy density lithium-ion batteries.

SnO-Sn3O4 heterostructural gas sensor with high response and selectivity to parts-per-billion-level NO2 at low operating temperature.

Considering the harmfulness of nitrogen dioxide (NO2), it is important to develop NO2 sensors with high responses and low limits of detection. In this study, we synthesize a novel SnO-Sn3O4 heterostructure through a one-step solvothermal method, which is used for the first time as an NO2 sensor. The material exhibits three-dimensional flower-like microparticles assembled by two-dimensional nanosheets, in situ-formed SnO-Sn3O4 heterostructures, and large specific surface area. Gas sensing measurements show that the responses of the SnO-Sn3O4 heterostructure to 500 ppb NO2 are as high as 657.4 and 63.4 while its limits of detection are as low as 2.5 and 10 parts per billion at 75 °C and ambient temperature, respectively. In addition, the SnO-Sn3O4 heterostructure has an excellent selectivity to NO2, even if exposed to mixture gases containing interferential part with high concentration. The superior sensing properties can be attributed to the in situ formation of SnO-Sn3O4 p-n heterojunctions and large specific surface area. Therefore, the SnO-Sn3O4 heterostructure having excellent NO2 sensing performances is very promising for applications as an NO2 sensor or alarm operated at a low operating temperature.

Precision-Trimming 2D Inverse-Opal Lattice on Elastomer to Ordered Nanostructures with Variable Size and Morphology.

A low-cost and scalable method is developed for producing large-area elastomer surfaces having ordered nanostructures with a variety of lattice features controllable to nanometer precision. The method adopts the known technique of molding a PDMS precursor film with a close-packed monolayer of monodisperse submicron polystyrene beads on water to form an inverse-opal dimple lattice with the dimple size controlled by the bead selection and the dimple depth by the molding condition. The subsequent novel precision engineering of the inverse-opal lattice comprises trimming the PDMS precursor by a combination of polymer curing temperature/time and polymer dissolution parameters. The resultant ordered surface nanostructures, fabricated with an increasing degree of trimming, include (a) submicron hemispherical dimples with nanothin interdimple rims and walls; (b) nanocones with variable degrees of tip-sharpness by trimming off the top part of the nanothin interdimple walls; and (c) soup-plate-like submicron shallow dimples with interdimple rims and walls by anisotropically trimming off the nanocones and forming close-packed shallow dimples. As exemplars of industrial relevance of these lattice features, tunable Young's modulus and wettability are demonstrated.