RESUMO
Hard materials are being investigated all the time by combining transition metals with light elements. Combining a structure search with first-principles functional calculations, we first discovered three stable stoichiometric C-rich ruthenium carbides in view of three synthesis routes, namely, the ambient phases of Ru2C3 and RuC, and two high pressure phases of RuC4. There is a phase transition of RuC4 from the P3[combining macron]m1 structure to the R3[combining macron]m structure above 98 GPa. The calculations of elastic constants and phonon dispersions show their mechanical and dynamical stability. The large elastic modulus, high Debye temperature and the estimated hardness values suggest that these hard ruthenium carbides have good mechanical properties. The analyses of electronic structure and chemical bonding indicate that chemical bonding, not carbon content, is the key factor for the hardness in these metallic C-rich ruthenium carbides. The partial covalent Ru-C bonds and strong covalent C-C bonds are responsible for the high hardness. Moreover, the emergence of partial covalent Ru-Ru bonds can enhance the hardness of RuC, while the ionic Ru-Ru bonds can weaken the hardness of Ru2C3.
RESUMO
BACKGROUND: Nucleic acid hybridization is an extensively adopted principle in biomedical research, in which the performance of any hybridization-based method depends on the specificity of probes to their targets. To determine the optimal probe(s) for detecting target(s) from a sample cocktail, we developed a novel algorithm, which has been implemented into a web platform for probe designing. This probe design workflow is now upgraded to satisfy experiments that require a probe designing tool to take the increasing volume of sequence datasets. RESULTS: Algorithms and probe parameters applied in UPS 2.0 include GC content, the secondary structure, melting temperature (Tm), the stability of the probe-target duplex estimated by the thermodynamic model, sequence complexity, similarity of probes to non-target sequences, and other empirical parameters used in the laboratory. Several probe background options,Unique probe within a group,Unique probe in a specific Unigene set,Unique probe based on the pangenomic level, and Unique Probe in the user-defined genome/transcriptome, are available to meet the scenarios that the experiments will be conducted. Parameters, such as salt concentration and the lower-bound Tm of probes, are available for users to optimize their probe design query. Output files are available for download on the result page. Probes designed by the UPS algorithm are suitable for generating microarrays, and the performance of UPS-designed probes has been validated by experiments. CONCLUSIONS: The UPS 2.0 evaluates probe-to-target hybridization under a user-defined condition to ensure high-performance hybridization with minimal chance of non-specific binding at the pangenomic and genomic levels. The UPS algorithm mimics the target/non-target mixture in an experiment and is very useful in developing diagnostic kits and microarrays. The UPS 2.0 website has had more than 1,300 visits and 360,000 sequences performed the probe designing task in the last 30 months. It is freely accessible at http://array.iis.sinica.edu.tw/ups/. Screen cast: http://array.iis.sinica.edu.tw/ups/demo/demo.htm.
