Computational Criteria for Evaluating Polysulfide Cohesion, Solvation, and Stabilization: Approach for Screening Effective Anchoring Substrates

Utilizing the functional groups of carbon substrates or third-party additives to adhere lithium polysulfides for suppressing their dissolution has been demonstrated to be capable of improving the sulfur cathode stability of lithium–sulfur batteries. In the present first-principles study, we systematically investigated the competitions between polysulfide self-cohesion, solvation, and its anchoring strengths on substrates. The dissolution probability of polysulfides in ether-based electrolytes is evaluated by a defined solvation potential Δ<i>P</i>_S‑C, which confirms that Li₂S₈ is the most soluble species; the competition of Li₂S₈ anchoring strength on different substrates and its solvation energy is described by a stabilizing potential Δ<i>P</i>_S‑A, which can be used to verify if a certain substrate can effectively stabilize polysulfides in cathodes. Two properties for a feasible substrate, containing affinitive sites with high electron density for anchoring polysulfides and containing sufficient affinitive sites to provide multiple interactions for enhancing the stabilization, are necessarily proposed. Accordingly, phosphorylated chitosan, among several substrates, is predicted to be a promising third-party substrate to preserve polysulfides in cathodes and prevent them from being dissolved. Our computational scheme may provide a reliable procedure for rapidly screening most appropriate candidates for designing the novel architecture of sulfur cathodes

Anchoring Lithium Polysulfides via Affinitive Interactions: Electrostatic Attraction, Hydrogen Bonding, or in Parallel?

Stabilizing lithium polysulfides in cathodes via interactions between polysulfides and affinitive functional groups could prevent polysulfide dissolution, leading to suppressed “shuttle effect” of lithium/sulfur (Li/S) batteries. Herein, four deoxynucleotides (DNs), including <b>A</b> (adenine-DN), <b>T</b> (thymine-DN), <b>G</b> (guanine-DN), and <b>C</b> (cytosine-DN), which own rich polysulfide affinitive groups, are selected to model the anchoring environments of polysulfides. Using the most soluble Li₂S₈ as probe, our first-principles simulations suggest that the interactions between polysulfides and substrates are highly correlated to the charges of affinitive sites, H-bonding environments and structural tension. The contributions from each type of interactions are quasi-quantitatively assessed. The electrostatic attractions between Li⁺ and the strong electron lone-pairs dominate the adsorption energetics, while the H-bonds formed between S₈^2– and substrate give rise to excessive stabilization. In contrast, structural distortion or rearrangement of the substrates is detrimental to the anchoring strengths. The quasi-quantitative resolution on the different interaction modes provides a facile and rational scheme for screening more efficient polysufide affinitive additives to sustain the cathode cyclicity of Li/S batteries

DataSheet_1_Evaluation of the peritumoral features using radiomics and deep learning technology in non-spiculated and noncalcified masses of the breast on mammography.pdf

ObjectiveTo assess the significance of peritumoral features based on deep learning in classifying non-spiculated and noncalcified masses (NSNCM) on mammography.MethodsWe retrospectively screened the digital mammography data of 2254 patients who underwent surgery for breast lesions in Harbin Medical University Cancer Hospital from January to December 2018. Deep learning and radiomics models were constructed. The classification efficacy in ROI and patient levels of AUC, accuracy, sensitivity, and specificity were compared. Stratified analysis was conducted to analyze the influence of primary factors on the AUC of the deep learning model. The image filter and CAM were used to visualize the radiomics and depth features.ResultsFor 1298 included patients, 771 (59.4%) were benign, and 527 (40.6%) were malignant. The best model was the deep learning combined model (2 mm), in which the AUC was 0.884 (P 60 years, and breast composition type B (P ConclusionCombining the tumoral and peritumoral features resulted in better identification of malignant NSNCM on mammography, and the performance of the deep learning model exceeded the radiomics model. Age, tumor size, and the breast composition type are essential for diagnosis.</p

Tailoring the Fluorescence of AIE-Active Metal–Organic Frameworks for Aqueous Sensing of Metal Ions

A hydroxyl-functionalized ligand was designed for the construction of metal–organic framework (MOF) materials with the aggregation-induced emission (AIE) feature, in which the fluorescence can be deliberately tailored: quenching the fluorescence to an “off” state by the decoration with heterocyclic auxiliary ligand 4,4′-bypyridine (Bpy) in the framework as a quenching agent and triggering the enhanced fluorescence to an “on” state by removal of Bpy through the metal competitive coordination substitution strategy. Our study shows that the occurrence of exciton migration between the AIE linker and conjugated auxiliary ligand Bpy causes fluorescence quenching. Time-dependent density functional theory was employed to understand the photoinduced electron transfer process and explain the origins of fluorescence quenching. Using this strategy, the prepared MOF material can perform as a fluorescence “off–on” probe for highly sensitive detection of Al³⁺ in aqueous media. The hydroxyl group plays a crucial role in sensing as it can selectively chelate Al³⁺, which is directly related to the dissociation of nonfluorescent MOF and consequent activation of the AIE process

Nonlinear-Optical Behaviors of a Chiral Metal–Organic Framework Comprised of an Unusual Multioriented Double-Helix Structure

We present here the synthesis of one enantiomeric pair of metal–organic framework materials comprised of a unique multioriented double-helix structure from an achiral spirocenter ligand. Our study clearly shows that the chiral MOF material encompasses concurrently multiple nonlinear-optical functions in the solid state: the noncentrosymmetric structural feature brings the chiral MOF high second-harmonic-generation efficiency; the incorporation of the spirocenter ligand can efficiently produce two-photon-excited photoluminescence with a larger-action cross-sectional value

Additional file 1 of Model containing sarcopenia and visceral adiposity can better predict the prognosis of hepatocellular carcinoma: a multicenter study

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