Taoran Li

Abstract Several critical issues, such as the shuttling effect and the sluggish reaction kinetics, exist in the design of high‐performance lithium–sulfur (Li‐S) batteries. Here, it is reported that nitrogen doping can simultaneously and significantly improve both the immobilization and catalyzation effects of Co 9 S 8 nanoparticles in Li‐S batteries. Combining the theoretical calculations with experimental investigations, it is revealed that nitrogen atoms can increase the binding energies between LiPSs and Co 9 S 8 , and as well as alleviate the sluggish kinetics of Li‐S chemistry in the Li 2 S 6 cathode. The same effects are also observed when adding N‐Co 9 S 8 nanoparticles into the commercial Li 2 S cathode (which has various intrinsic advantages, but unfortunately a high overpotential). A remarkable improvement in the battery performances in both cases is observed. The work brings heteroatom‐doped Co 9 S 8 to the attention of designing high‐performance Li‐S batteries. A fundamental understanding of the inhibition of LiPSs shuttle and the catalytic effect of Li 2 S in the newly developed system may encourage more effort along this interesting direction.

Lithium-sulfur (Li-S) batteries have attracted widespread attention due to their high theoretical energy density. However, their practical application is still hindered by the shuttle effect and the sluggish conversion of lithium polysulfides (LiPSs). Herein, monodisperse molybdenum (Mo) nanoparticles embedded onto nitrogen-doped graphene (Mo@N-G) were developed and used as a highly efficient electrocatalyst to enhance LiPS conversion. The weight ratio of the electrocatalyst in the catalyst/sulfur cathode is only 9%. The unfilled d orbitals of oxidized Mo can attract the electrons of LiPS anions and form Mo–S bonds during the electrochemical process, thus facilitating fast conversion of LiPSs. Li-S batteries based on the Mo@N-G/S cathode can exhibit excellent rate performance, large capacity, and superior cycling stability. Moreover, Mo@N-G also plays an important role in room-temperature quasi-solid-state Li-S batteries. These interesting findings suggest the great potential of Mo nanoparticles in building high-performance Li-S batteries.

INTRODUCTION: Subjective cognitive decline (SCD) represents a cognitively normal state but at an increased risk for developing Alzheimer's disease (AD). Recognizing the glucose metabolic biomarkers of SCD could facilitate the location of areas with metabolic changes at an ultra-early stage. The objective of this study was to explore glucose metabolic biomarkers of SCD at the region of interest (ROI) level. METHODS: This study was based on cohorts from two tertiary medical centers, and it was part of the SILCODE project (NCT03370744). Twenty-six normal control (NC) cases and 32 SCD cases were in cohort 1; 36 NCs, 23 cases of SCD, 32 cases of amnestic mild cognitive impairment (aMCIs), 32 cases of AD dementia (ADDs), and 22 cases of dementia with Lewy bodies (DLBs) were in cohort 2. Each subject underwent [18F]fluoro-2-deoxyglucose positron emission tomography (PET) imaging and magnetic resonance imaging (MRI), and subjects from cohort 1 additionally underwent amyloid-PET scanning. The ROI analysis was based on the Anatomical Automatic Labeling (AAL) template; multiple permutation tests and repeated cross-validations were conducted to determine the metabolic differences between NC and SCD cases. In addition, receiver operating characteristic curves were used to evaluate the capabilities of potential glucose metabolic biomarkers in distinguishing different groups. Pearson correlation analysis was also performed to explore the correlation between glucose metabolic biomarkers and neuropsychological scales or amyloid deposition. RESULTS: Only the right middle temporal gyrus (RMTG) passed the methodological verification, and its metabolic levels were correlated with the degrees of complaints (R = - 0.239, p = 0.009), depression (R = - 0.200, p = 0.030), and abilities of delayed memory (R = 0.207, p = 0.025), and were weakly correlated with cortical amyloid deposition (R = - 0.246, p = 0.066). Furthermore, RMTG metabolism gradually decreased across the cognitive continuum, and its diagnostic efficiency was comparable (NC vs. ADD, aMCI, or DLB) or even superior (NC vs. SCD) to that of the metabolism of the posterior cingulate cortex or precuneus. CONCLUSIONS: These findings suggest that the hypometabolism of RMTG could be a typical feature of SCD, and the large-scale hypometabolism in patients with symptomatic stages of AD may start from the RMTG, which gradually progresses starting in the preclinical stage. The specificity of identifying SCD from the perspective of self-perceived symptoms is likely to be increased by the detection of RMTG metabolism.