Regulating the electronic structure of Pt SAs-Ni2P for enhanced hydrogen evolution reaction.

The single atom catalysts (SACs) show immense promise as catalytic materials. By doping the single atoms (SAs) of precious metals onto substrates, the atomic utilization of these metals can be maximized, thereby reducing catalyst costs. The electronic structure of precious metal SAs is significantly influenced by compositions of doped substrates. Therefore, optimizing the electronic structure through appropriate doping of substrates can further enhance catalytic activity. Here, Pt single atoms (Pt SAs) are doped onto transition metal sulfide substrate NiS2 (Pt SAs-NiS2) and phosphide substrate Ni2P (Pt SAs-Ni2P) to design and prepare catalysts. Compared to the Pt SAs-NiS2 catalyst, the Pt SAs-Ni2P catalyst exhibits better hydrogen evolution catalytic performance and stability. Under 1 M KOH conditions, the hydrogen evolution mass activity current density of the Pt SAs-Ni2P catalyst reaches 0.225 A mgPt-1 at 50 mV, which is 33 times higher than that of commercial Pt/C catalysts. It requires only 44.9 mV to achieve a current density of 10 mA cm-2. In contrast, for the Pt SAs-NiS2 catalyst, the hydrogen evolution mass activity current density is 0.178 A mgPt-1, requiring 77.8 mV to achieve a current density of 10 mA cm-2. Theoretical calculations indicate that in Pt SAs-Ni2P, the interaction between Pt SAs and the Ni2P substrate causes the Pt d-band center to shift downward, enhancing the H2O desorption and providing optimal H binding sites. Additionally, the hollow octahedral morphology of Ni2P provides a larger surface area, exposing more reactive sites and improving reaction kinetics. This study presents an effective pathway for preparing high-performance hydrogen evolution electrocatalysts by selecting appropriate doped substrates to control the electronic structure of Pt SAs.

Optimization of mid-infrared noninvasive blood-glucose prediction model by support vector regression coupled with different spectral features.

Mid-infrared spectral analysis of glucose in subcutaneous interstitial fluid has been widely employed as a noninvasive alternative to the standard blood-glucose detection requiring blood-sampling via skin-puncturing, but improving the confidence level of such a replacement remains highly desirable. Here, we show that with an innovative metric of attributes in measurements and data-management, a high accuracy in correlating the test results of our improved spectral analysis to those of the standard detection is accomplished. First, our comparative laser speckle contrast imaging of subcutaneous interstitial fluid in fingertips, thenar and hypothenar reveal that spectral measurements from hypothenar, with an attenuated total reflection Fourier transform infrared spectrometer, give much stronger signals than the stereotype measurements from fingertips. Second, we demonstrate that discriminative selection of the spectral locations and ranges, to minimize spectral interference and maximize signal-to-noise, are critically important. The optimal band is pinned at that between 1000 ± 3 cm-1 and1040 ± 3 cm-1. Third, we propose an individual exclusive prediction model by adopting the support vector regression analysis of the spectral data from four subjects. The average predicted coefficient of determination, root mean square error and mean absolute error of four subjects are 0.97, 0.21 mmol/L, 0.17 mmol/L, respectively, and the average probability of being in Zone A of the Clark error grid is 100.00 %. Additionally, we demonstrate with the Bland and Altman plot that our proposed model has the highest consistency with portable blood glucose meter detection method.