The contributions of each digit force for the first PC.

<p>(A) <i>Fz</i> components of PC1, showing a relatively consistent pattern. (B) <i>Fy</i> components of PC1, showing great variability.</p

Force distribution pattern of the digits.

<p>(A) Distribution patterns for <i>Fy</i> and <i>Fz</i> of a normal grasp posture in the holding stable phase (HSP) from the average data of all participants. (B) Radar plot for comparing the distribution patterns of the force in the <i>Fz</i> direction in finger-restricted trials and normal grasp condition. (<i>TFz</i>: <i>Fz</i> of thumb. <i>IFz</i>: <i>Fz</i> of index finger. <i>MFz</i>: <i>Fz</i> of middle finger. <i>RFz</i>: <i>Fz</i> of ring finger. <i>LFz</i>: <i>Fz</i> of little finger).</p

CV results of each digit and different grasp conditions from this study and a previous one [19].

<p>Values represented as Mean (SD).</p><p>Statistical tests: one-way ANOVA (*** indicates with statistical significance among groups via One-way ANOVA); post-hoc: Bonferroni’s <i>t</i>-test (* indicates with statistical significance between groups via Bonferroni’s <i>t</i>-test).</p><p>CV: coefficient of variation.</p><p>CV_T: coefficient of variation of the thumb.</p><p>CV_I: coefficient of variation of the index finger.</p><p>CV_M: coefficient of variation of the middle finger.</p><p>CV_R: coefficient of variation of the ring finger.</p><p>CV_L: coefficient of variation of the little finger.</p

The results of PCA.

<p>(A) For <i>Fz</i> of five digits in normal grasp posture: PC1 accounted for 97% of PVAF. (B) For <i>Fy</i> of five digits in normal grasp posture: PC1 accounted for 70% of PVAF.</p

<i>Fz</i> correlation coefficient for two digits in different posture trials during the FIP via the linear correlation test.

<p>Values represented as Mean (SD).</p

Experimental apparatus and testing procedure.

<p>(A) Glass simulator equipped with five force transducers. Each force transducer had its own force coordination system. <i>Fx</i>: tangential force vector in the clockwise direction; <i>Fy</i>: force vector along the central axis of the glass simulator in the anti-gravity direction; <i>Fz</i>: axial force toward the center axis of the glass simulator. (B) Cylindrical grasping with five fingers.</p

Distribution patterns of <i>Fy</i> and <i>Fz</i> in normal grasping posture.

<p>Values represented as Mean (SD).</p

13% Efficiency Hybrid Organic/Silicon-Nanowire Heterojunction Solar Cell <i>via</i> Interface Engineering

Interface carrier recombination currently hinders the performance of hybrid organic–silicon heterojunction solar cells for high-efficiency low-cost photovoltaics. Here, we introduce an intermediate 1,1-bis[(di-4-tolylamino)phenyl]cyclohexane (TAPC) layer into hybrid heterojunction solar cells based on silicon nanowires (SiNWs) and conjugate polymer poly(3,4-ethylenedioxy-thiophene):poly(styrenesulfonate) (PEDOT:PSS). The highest power conversion efficiency reaches a record 13.01%, which is largely ascribed to the modified organic surface morphology and suppressed saturation current that boost the open-circuit voltage and fill factor. We show that the insertion of TAPC increases the minority carrier lifetime because of an energy offset at the heterojunction interface. Furthermore, X-ray photoemission spectroscopy reveals that TAPC can effectively block the strong oxidation reaction occurring between PEDOT:PSS and silicon, which improves the device characteristics and assurances for reliability. These learnings point toward future directions for versatile interface engineering techniques for the attainment of highly efficient hybrid photovoltaics