Cylindrical Water Triboelectric Nanogenerator via Controlling Geometrical Shape of Anodized Aluminum for Enhanced Electrostatic Induction

We demonstrate a cylindrical water triboelectric nanogenerator (CW-TENG) that generates sustainable electrical output. The inner surface of the cylinder was patterned into superhydrophobic and hydrophilic parts to control water flow inside the packaged design of CW-TENG. Here, various thicknesses and roughnesses of the superhydrophobic surface, generated using aluminum oxide nanostructures for enhanced electrostatic induction, were measured to obtain the maximum output and superhydrophobicity. Also, we demonstrate the possibility of using a hydrophilic surface for energy harvesting and as a water reservoir in the packaged design

Adsorption Properties of MFM-400 and MFM-401 with CO₂ and Hydrocarbons: Selectivity Derived from Directed Supramolecular Interactions

([Sc₂(OH)₂(BPTC)]) (H₄BPTC = biphenyl-3,3′,5,5′-tetracarboxylic acid), MFM-400 (MFM = Manchester Framework Material, previously designated NOTT), and ([Sc­(OH)­(TDA)]) (H₂TDA = thiophene-2,5-dicarboxylic acid), MFM-401, both show selective and reversible capture of CO₂. In particular, MFM-400 exhibits a reasonably high CO₂ uptake at low pressures and competitive CO₂/N₂ selectivity coupled to a moderate isosteric heat of adsorption (<i>Q</i>_st) for CO₂ (29.5 kJ mol^–1) at zero coverage, thus affording a facile uptake–release process. Grand canonical Monte Carlo (GCMC) and density functional theory (DFT) computational analyses of CO₂ uptake in both materials confirmed preferential adsorption sites consistent with the higher CO₂ uptake observed experimentally for MFM-400 over MFM-401 at low pressures. For MFM-400, the Sc–OH group participates in moderate interactions with CO₂ (<i>Q</i>_st = 33.5 kJ mol^–1), and these are complemented by weak hydrogen-bonding interactions (O···H–C = 3.10–3.22 Å) from four surrounding aromatic −CH groups. In the case of MFM-401, adsorption is provided by cooperative interactions of CO₂ with the Sc–OH group and one C–H group. The binding energies obtained by DFT analysis for the adsorption sites for both materials correlate well with the observed moderate isosteric heats of adsorption for CO₂. GCMC simulations for both materials confirmed higher uptake of EtOH compared with nonpolar vapors of toluene and cyclohexane. This is in good correlation with the experimental data, and DFT analysis confirmed the formation of a strong hydrogen bond between EtOH and the hydrogen atom of the hydroxyl group of the MFM-400 and MFM-401 framework (FW) with H–O_EtOH···H–O_FW distances of 1.77 and 1.75 Å, respectively. In addition, the accessible regeneration of MFM-400 and MFM-401 and release of CO₂ potentially provide minimal economic and environmental penalties

Individualized prediction of mortality using multiple inflammatory markers in patients on dialysis

<div><p>This study aimed to evaluate whether the combination of inflammatory markers could provide predictive powers for mortality in individual patients on dialysis and develop a predictive model for mortality according to dialysis modality. Data for inflammatory markers were obtained at the time of enrollment from 3,309 patients on dialysis from a prospective multicenter cohort. Net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated. Cox proportional hazards regression analysis was used to derive a prediction model of mortality and the integrated area under the curve (iAUC) was calculated to compare the predictive accuracy of the models. The incremental additions of albumin, high-sensitive C-reactive protein (hsCRP), white blood count (WBC), and ferritin to the conventional risk factors showed the highest predictive powers for all-cause mortality in the entire population (NRI, 21.0; IDI, 0.045) and patients on peritoneal dialysis (NRI, 25.7; IDI, 0.061). The addition of albumin and hsCRP to the conventional risk factors markedly increased predictive powers for all-cause mortality in HD patients (NRI, 19.0; IDI, 0.035). The prediction model for all-cause mortality using conventional risk factors and combination of inflammatory markers with highest NRI value (iAUC, 0.741; 95% CI, 0.722–0.761) was the most accurate in the entire population compared with a model including conventional risk factors alone (iAUC, 0.719; 95% CI, 0.700–0.738) or model including only significant conventional risk factors and inflammatory markers (iAUC, 0.734; 95% CI, 0.714–0.754). Using multiple inflammatory markers practically available in a clinic can provide higher predictive power for all-cause mortality in patients on dialysis. The predictive model for mortality based on combinations of inflammatory markers enables a stratified risk assessment. However, the optimal combination for the predictive model was different in each dialysis modality.</p></div

Time-dependent receiver operating characteristic curves for all-cause mortality for patients on dialysis according to dialysis modality.

<p>In the entire population (A), iAUC values for all-cause mortality were 0.720 (95% CI, 0.700–0.739) for the crude model, including conventional risk factors, 0.724 (95% CI, 0.705–0.744) for the crude model plus WBC, 0.726 (95% CI, 0.707–0.745) for the crude model plus hsCRP, 0.737 (95% CI, 0.717–0.756) for the crude model plus albumin, 0.742 (95% CI, 0.721–0.762) for the crude model plus albumin, hsCRP, WBC, and ferritin. The differences in iAUC were -0.0046 (-0.010 to -0.001) for WBC, -0.006 (-0.012 to -0.002) for hsCRP, -0.017 (-0.028 to -0.009) for albumin, -0.022 (95% CI, -0.033 to -0.013) for albumin, hsCRP, WBC, and ferritin, demonstrating that although individual inflammatory markers significantly improved the predictive accuracy for all-cause mortality, the integration of all inflammatory markers resulted in the most accurate prediction model. In patients on HD (B), iAUC values for all-cause mortality were 0.717 (95% CI, 0.693–0.741) for the crude model, 0.722 (95% CI, 0.698–0.743) for the crude model plus WBC, 0.723 (95% CI, 0.698–0.747) for the crude model plus hsCRP, 0.733 (95% CI, 0.710–0.755) for the crude model plus albumin, 0.735 (95% CI, 0.712–0.759) for the crude model plus albumin, hsCRP, WBC, and ferritin. The differences in iAUC were -0.0043 (-0.010 to -0.0004) for WBC, -0.005 (-0.012 to -0.0006) for hsCRP, -0.015 (-0.027 to -0.007) for albumin, -0.018 (95% CI, -0.030 to -0.008) for albumin, hsCRP, WBC, and ferritin. In patients on PD (C), iAUC values for all-cause mortality were 0.778 (95% CI, 0.743–0.812) for the crude model, 0.783 (95% CI, 0.749–0.817) for the crude model plus WBC, 0.789 (95% CI, 0.755–0.821) for the crude model plus hsCRP, 0.787 (95% CI, 0.753–0.821) for the crude model plus albumin, 0.799 (95% CI, 0.768–0.832) for the crude model plus albumin, hsCRP, WBC, and ferritin. The differences in iAUC were -0.004 (-0.015 to 0.0003) for WBC, -0.010 (-0.025 to -0.002) for hsCRP, -0.009 (-0.023 to -0.0003) for albumin, -0.021 (95% CI, -0.038 to -0.007) for albumin, hsCRP, WBC, and ferritin.</p

Multivariate adjusted hazard ratios in all-cause, cardiovascular, and infection-related mortality.

<p>Multivariate adjusted hazard ratios in all-cause, cardiovascular, and infection-related mortality.</p

Causes of death of patients on dialysis according to dialysis modality.

<p>Causes of death of patients on dialysis according to dialysis modality.</p

Baseline demographic, clinical, and biochemical characteristics according to dialysis modality.

<p>Baseline demographic, clinical, and biochemical characteristics according to dialysis modality.</p

Hazard ratios of each variable and comparing the predictive accuracy of the models.

<p>Hazard ratios of each variable and comparing the predictive accuracy of the models.</p