No abstract

Purpose Deep phenotyping is an emerging trend in precision medicine for genetic disease. The shape of the face is affected in 30–40% of known genetic syndromes. Here, we determine whether syndromes can be diagnosed from 3D images of human faces. Methods We analyzed variation in three-dimensional (3D) facial images of 7057 subjects: 3327 with 396 different syndromes, 727 of their relatives, and 3003 unrelated, unaffected subjects. We developed and tested machine learning and parametric approaches to automated syndrome diagnosis using 3D facial images. Results Unrelated, unaffected subjects were correctly classified with 96% accuracy. Considering both syndromic and unrelated, unaffected subjects together, balanced accuracy was 73% and mean sensitivity 49%. Excluding unrelated, unaffected subjects substantially improved both balanced accuracy (78.1%) and sensitivity (56.9%) of syndrome diagnosis. The best predictors of classification accuracy were phenotypic severity and facial distinctiveness of syndromes. Surprisingly, unaffected relatives of syndromic subjects were frequently classified as syndromic, often to the syndrome of their affected relative. Conclusion Deep phenotyping by quantitative 3D facial imaging has considerable potential to facilitate syndrome diagnosis. Furthermore, 3D facial imaging of “unaffected” relatives may identify unrecognized cases or may reveal novel examples of semidominant inheritance.

We investigated the effect of single and multidopants on the thermoelectrical properties of host ZnO films. Incorporation of the single dopant Ga in the ZnO films improved the conductivity and mobility but lowered the Seebeck coefficient. Dual Ga- and In-doped ZnO thin films show slightly decreased electrical conductivity but improved Seebeck coefficient. The variation of thermoelectric properties is discussed in terms of film crystallinity, which is subject to the dopants' radius. Small amounts of In dopants with a large radius may introduce localized regions in the host film, affecting the thermoelectric properties. Consequently, a 1.5 times increase in power factor, three times reduction in thermal conductivity, and 5-fold enhancement in the figure of merit ZT have been achieved at 110 °C. The results also indicate that the balanced control of both electron and lattice thermal conductivities through dopant selection are necessary to attain low total thermal conductivity.

No abstract

No abstract

No abstract

Developing highly efficient and durable hydrogen evolution reaction (HER) electrocatalysts is crucial for addressing the energy and environmental challenges. Among the 2D-layered chalcogenides, MoSe2 possesses superior features for HER catalysis. The van der Waals attractions and high surface energy, however, stack the MoSe2 layers, resulting in a loss of edge active catalytic sites. In addition, MoSe2 suffers from low intrinsic conductivity and weak electrical contact with active sites. To overcome the issues, this work presents a novel approach, wherein the in situ incorporated diethylene glycol solvent into the interlayers of MoSe2 during synthesis when treated thermally in an inert atmosphere at 600 °C transformed into graphene (Gr). This widened the interlayer spacing of MoSe2, thereby exposing more HER active edge sites with high conductivity offered by the incorporated Gr. The resulting MoSe2-Gr composite exhibited a significantly enhanced HER catalytic activity compared to the pristine MoSe2 in an acidic medium and demonstrated a superior HER catalytic activity compared to the state-of-the-art Pt/C catalyst, particularly at a high current density beyond ca. 55 mA cm−2. Additionally, the MoSe2-Gr catalyst demonstrated long-term electrochemical stability during HER. This work, thus, presents a facile and novel approach for obtaining an efficient MoSe2 electrocatalyst applicable in green hydrogen production.

We present an ab initio study of carbon and nitrogen substituting oxygen in zinc oxide structure. Detailed spin-polarized total-energy calculations of the various defect and dopant at different charge states and geometries indicate a non-zero spin magnetic moment only found from the CO-2 while NO shows no sign of localized magnetic moment. It is also revealed that CO has a tendency towards forming C2 complexes inside the ZnO structure with very weak antiferromagnetic spin arrangement. Furthermore, it was found that oxygen vacancy and hydrogen interstitial could not induce ferromagnetism in C doped ZnO.