Integrated Oxygen-Constraining Strategy for Ni-Rich Layered Oxide Cathodes.

Surface engineering is sought to stabilize nickel-rich layered oxide cathodes in high-energy-density lithium-ion batteries, which suffer from severe surface oxygen loss and rapid structure degradation, especially during deep delithiation at high voltages or high temperatures. Here, we propose a well-designed oxygen-constraining strategy to address the crisis of oxygen evolution. By integrating a La, Fe gradient diffusion layer and a LaFeO coating into the Ni-rich layered particles, along with incorporating an antioxidant binder into the electrodes, three progressive lines of defense are constructed: immobilizing the lattice oxygen at the subsurface, blocking the released oxygen at the interface, and capturing the residual singlet oxygen on the external surface.

Can human-machine feedback in a smart learning environment enhance learners' learning performance? A meta-analysis.

Objective: The human-machine feedback in a smart learning environment can influences learners' learning styles, ability enhancement, and affective interactions. However, whether it has stability in improving learning performance and learning processes, the findings of many empirical studies are controversial. This study aimed to analyze the effect of human-machine feedback on learning performance and the potential boundary conditions that produce the effect in a smart learning environment.

Enhancing the Initial Coulombic Efficiency of Sodium-Ion Batteries via Highly Active Na S as Presodiation Additive.

Recently, sodium-ion batteries (SIBs) have received considerable attention for large-scale energy storage applications. However, the low initial Coulombic efficiency of traditional SIBs severely impedes their further development. Here, a highly active Na S-based composite is employed as a self-sacrificial additive for sodium compensation in SIBs.

Interface Engineering via Regulating Electrolyte for High-Voltage Layered Oxide Cathodes-Based Li-Ion Batteries.

Li-rich and Ni-rich layered oxides as next-generation high-energy cathodes for lithium-ion batteries (LIBs) possess the catalytic surface, which leads to intensive interfacial reactions, transition metal ion dissolution, gas generation, and ultimately hinders their applications at 4.7 V. Here, robust inorganic/organic/inorganic-rich architecture cathode-electrolyte interphase (CEI) and inorganic/organic-rich architecture anode-electrolyte interphase (AEI) with F-, B-, and P-rich inorganic components through modulating the frontier molecular orbital energy levels of lithium salts are constructed.

Application of Machine Learning Techniques to Detect the Children with Autism Spectrum Disorder.

Early detection of autism spectrum disorder (ASD) is highly beneficial to the health sustainability of children. Existing detection methods depend on the assessment of experts, which are subjective and costly. In this study, we proposed a machine learning approach that fuses physiological data (electroencephalography, EEG) and behavioral data (eye fixation and facial expression) to detect children with ASD.

Early Onset of Impairments of Interpersonal Motor Synchrony in Preschool-Aged Children with Autism Spectrum Disorder.

Characteristics of interpersonal motor synchrony in individuals with autism spectrum disorder (ASD) have been investigated only in older children and adolescents, which calls for investigations in younger samples. The interpersonal motor synchrony was compared between preschool-aged children with (n = 23) and without ASD (n = 24) during free plays with familiar teachers. Children with ASD exhibited reduced synchrony of the upper body and trunk compared with typically developing (TD) children.