Substrate co-doping modulates electronic metal-support interactions and significantly enhances single-atom catalysis

Transitional metal nanoparticles or atoms deposited on appropriate substrates can lead to highly economical, efficient, and selective catalysis. One of the greatest challenges is to control the electronic metal–support interactions (EMSI) between the supported metal atoms and the substrate so as to optimize their catalytic performance. Here, from first-principles calculations, we show that an otherwise inactive Pd single adatom on TiO2(110) can be tuned into a highly effective catalyst, e.g. for O2 adsorption and CO oxidation, by purposefully selected metal–nonmetal co-dopant pairs in the substrate. Such an effect is proved here to result unambiguously from a significantly enhanced EMSI. A nearly linear correlation is noted between the strength of the EMSI and the activation of the adsorbed O2 molecule, as well as the energy barrier for CO oxidation. Particularly, the enhanced EMSI shifts the frontier orbital of the deposited Pd atom upward and largely enhances the hybridization and charge transfer between the O2 molecule and the Pd atom. Upon co-doping, the activation barrier for CO oxidation on the Pd monomer is also reduced to a level comparable to that on the Pd dimer which was experimentally reported to be highly efficient for CO oxidation. The present findings provide new insights into the understanding of the EMSI in heterogeneous catalysis and can open new avenues to design and fabricate cost-effective single-atom-sized and/or nanometer-sized catalysts

Bubble Behavior and Heat Transfer in Quasi-Steady Pool Boiling in Microgravity

Pool boiling of degassed FC-72 on a plane plate heater has been studied experimentally in microgravity. A quasi-steady heating method is adopted, in which the heating voltage is controlled to increase exponentially with time. Compared with terrestrial experiments, bubble behaviors are very different, and have direct effect on heat transfer. Small, primary bubbles attached on the surface seem to be able to suppress the activation of the cavities in the neighborhoods, resulting in a slow increase of the wall temperature with the heat flux. For the high subcooling, the coalesced bubble has a smooth surface and a small size. It is difficult to cover the whole heater surface, resulting in a special region of gradual transitional boiling in which nucleate boiling and local dry area can co-exist. No turning point corresponding to the transition from nucleate boiling to film boiling can be observed. On the contrary, the surface oscillation of the coalesced bubble at low subcooling may cause more activated nucleate sites, and then the surface temperature may keep constant or even fall down with the increasing heat flux. Furthermore, an abrupt transition to film boiling can also be observed. It is shown that heat transfer coefficient and CHF increase with the subcooling or pressure in microgravity, as observed in normal gravity

Identification and validation of oncologic miRNA biomarkers for Luminal A-like breast cancer

Introduction: Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting. Methods: Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n=54) and controls (n=56). RNA was extracted, reverse transcribed and subjected to microarray analysis (n=10 Luminal A-like; n=10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n=44 Luminal A; n=46 Control) and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated. Results: Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis ( miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652 ). The biomarker potential of 4 miRNAs ( miR-29a, miR-181a , miR-223 and miR-652 ) was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p=0.001, 0.004, 0.009 and 0.004 respectively). Binary logistic regression confirmed that combination of 3 of these miRNAs ( miR-29a, miR-181a and miR-652 ) could reliably differentiate between cancers and controls with an AUC of 0.80. Conclusion: This study provides insight into the underlying molecular portrait of Luminal A-like breast cancer subtype. From an initial 76 miRNAs, 4 were validated with altered expression in the blood of women with Luminal A-like breast cancer. The expression profiles of these 3 miRNAs, in combination with mammography, has potential to facilitate accurate subtype- specific breast tumor detection

SPOT-Seq-RNA: Predicting protein-RNA complex structure and RNA-binding function by fold recognition and binding affinity prediction

RNA-binding proteins (RBPs) play key roles in RNA metabolism and post-transcriptional regulation. Computational methods have been developed separately for prediction of RBPs and RNA-binding residues by machine-learning techniques and prediction of protein-RNA complex structures by rigid or semiflexible structure-to-structure docking. Here, we describe a template-based technique called SPOT-Seq-RNA that integrates prediction of RBPs, RNA-binding residues, and protein-RNA complex structures into a single package. This integration is achieved by combining template-based structure-prediction software, SPARKS X, with binding affinity prediction software, DRNA. This tool yields reasonable sensitivity (46 %) and high precision (84 %) for an independent test set of 215 RBPs and 5,766 non-RBPs. SPOT-Seq-RNA is computationally efficient for genome-scale prediction of RBPs and protein-RNA complex structures. Its application to human genome study has revealed a similar sensitivity and ability to uncover hundreds of novel RBPs beyond simple homology. The online server and downloadable version of SPOT-Seq-RNA are available at http://sparks-lab.org/server/SPOT-Seq-RNA/

An oxidized magnetic Au single atom on doped TiO2(110) becomes a high performance CO oxidation catalyst due to the charge effect

Catalysis using gold nanoparticles supported on oxides has been under extensive investigation for many important application processes. However, how to tune the charge state of a given Au species to perform a specific chemical reaction, e.g. CO oxidation, remains elusive. Here, using first-principles calculations, we show clearly that an intrinsically inert Au anion deposited on oxygen-deficient TiO2(110) (Au@TiO2(110)) can be tuned and optimized into a highly effective single atom catalyst (SAC), due to the depletion of the d-orbital by substrate doping. Particularly, Ni- and Cu-doped Au@TiO2 complexes undergo a reconstruction driven by one of the two dissociated O atoms upon CO oxidation. The remaining O atom heals the surface oxygen vacancy and results in a stable bow-shaped surface “O–Au–O” species; thereby the highly oxidized Au single atom now exhibits magnetism and dramatically enhanced activity and stability for O2 activation and CO oxidation, due to the emergence of high density of states near the Fermi level. Based on further extensive calculations, we establish the “charge selection rule” for O2 activation and CO oxidation on Au: the positively charged Au SAC is more active than its negatively charged counterpart for O2 activation, and the more positively charged the Au, the more active it is

Fe3O4–Au and Fe2O3–Au Hybrid Nanorods: Layer-by-Layer Assembly Synthesis and Their Magnetic and Optical Properties

A layer-by-layer technique has been developed to synthesize FeOOH–Au hybrid nanorods that can be transformed into Fe2O3–Au and Fe3O4–Au hybrid nanorods via controllable annealing process. The homogenous deposition of Au nanoparticles onto the surface of FeOOH nanorods can be attributed to the strong electrostatic attraction between metal ions and polyelectrolyte-modified FeOOH nanorods. The annealing atmosphere controls the phase transformation from FeOOH–Au to Fe3O4–Au and α-Fe2O3–Au. Moreover, the magnetic and optical properties of as-synthesized Fe2O3–Au and Fe3O4–Au hybrid nanorods have been investigated