Molecular fingerprint and machine learning to accelerate design of high-performance homochiral metal–organic frameworks

Computational screening was employed to calculate the enantioseparation capabilities of 45 functionalized homochiral metal–organic frameworks (FHMOFs), and machine learning (ML) and molecular fingerprint (MF) techniques were used to find new FHMOFs with high performance. With increasing temperature, the enantioselectivities for (R,S)-1,3-dimethyl-1,2-propadiene are improved. The “glove effect” in the chiral pockets was proposed to explain the correlations between the steric effect of functional groups and performance of FHMOFs. Moreover, the neighborhood component analysis and RDKit/MACCS MFs show the highest predictive effect on enantioselectivities among the four ML classification algorithms with nine MFs that were tested. Based on the importance of MF, 85 new FHMOFs were designed, and a newly designed FHMOF, NO₂-NHOH-FHMOF, with high similarity to the optimal MFs achieved improved chiral separation performance, with enantioselectivities of 85%. The design principles and new chiral pockets obtained by ML and MFs could facilitate the development of new materials for chiral separation.     

In situ Y2Si2O7 coatings on SiC fibers: Thermodynamic analysis and processing

It is shown using thermodynamic analysis and kinetic modeling that a processing window exists for the formation of Y₂Si₂O₇ coatings on SiC. The proposed method is validated using an experimental procedure in which the in situ formation of Y₂Si₂O₇ on a commercial SiC-based fiber is demonstrated. The method involves the deposition of YPO₄ on preoxidized fine diameter SiC-based fibers, and heat treating the coated fibers within a calculated processing window of oxygen partial pressure, temperature, degree of preoxidation, and coating thickness. The results are promising for the development of environmentally resistant interfacial coatings for SiC-fiber reinforced SiC-based matrix composites. The proposed and validated approach allows a low-cost method to obtain continuous hermetic coatings on SiC fibers with interfacial properties adequate for tough composite behavior that resists degradation under turbine engine conditions.     

The three Rs of river ecosystem resilience: Resources,recruitment, and refugia

Resilience in river ecosystems requires that organisms must persist in the face of highly dynamic hydrological and geomorphological variations. Disturbance events such as floods and droughts are postulated to shape life history traits that support resilience, but river management and conservation would benefit from greater understanding of the emergent effects in communities of river organisms. We unify current knowledge of taxonomic‐, phylogenetic‐, and trait‐based aspects of river communities that might aid the identification and quantification of resilience mechanisms. Temporal variations in river productivity, physical connectivity, and environmental heterogeneity resulting from floods and droughts are highlighted as key characteristics that promote resilience in these dynamic ecosystems. Three community‐wide mechanisms that underlie resilience are (a) partitioning (competition/facilitation) of dynamically varying resources, (b) dispersal, recolonization, and recruitment promoted by connectivity, and (c) functional redundancy in communities promoted by resource heterogeneity and refugia. Along with taxonomic and phylogenetic identity, biological traits related to feeding specialization, dispersal ability, and habitat specialization mediate organism responses to disturbance. Measures of these factors might also enable assessment of the relative contributions of different mechanisms to community resilience. Interactions between abiotic drivers and biotic aspects of resource use, dispersal, and persistence have clear implications for river conservation and management. To support these management needs, we propose a set of taxonomic, phylogenetic, and life‐history trait metrics that might be used to measure resilience mechanisms. By identifying such indicators, our proposed framework can enable targeted management strategies to adapt river ecosystems to global change.     

Computer-based engineering of thermostabilized antibody fragments

We used the molecular modeling program Rosetta to identify clusters of amino acid substitutions in antibody fragments (scFvs and scAbs) that improve global protein stability and resistance to thermal deactivation. Using this methodology, we increased the melting temperature (T_m) and resistance to heat treatment of an antibody fragment that binds to the Clostridium botulinum hemagglutinin protein (anti-HA33). Two designed antibody fragment variants with two amino acid replacement clusters, designed to stabilize local regions, were shown to have both higher T_m compared to the parental scFv and importantly to retain full antigen binding activity after 2 hr of incubation at 70°C. The crystal structure of one thermostabilized scFv variants was solved at 1.6 Å and shown to be in close agreement with the RosettaAntibody model prediction.     

Ethnography,CSCW and Ethnomethodology

Computer Supported Cooperative Work (CSCW) - This paper documents some details and some examples of the influence of ethnomethodological work in the fieldwork tradition associated with European...     

Structural dependence of chemical durability in modified aluminoborate glasses

Alkali and alkaline earth aluminoborate glasses feature high resistance to cracking under sharp contact loading compared to other oxide glasses. However, due to the high content of hygroscopic B₂O₃, it is expected that applications of these glasses could be hindered by poor chemical durability in aqueous solutions. Indeed, the compositional and structural dependence of their dissolution kinetics remains unexplored. In this work, we correlate the dissolution rates of aluminoborate glasses in acidic, neutral, and basic solutions with the structural changes induced by varying the aluminum-to-boron ratio. In detail, we investigate a total of seventeen magnesium, lithium, and sodium aluminoborate glasses with fixed modifier content of 25 mol%. We show that the structural changes induced by alumina depend on the network modifier. We also demonstrate a correlation between the chemical durability at various pH values and the structural changes in Mg-, Li- and Na-aluminoborate glasses. The substitution of alumina by boron oxide leads to a general decrease in chemical corrosion in neutral and acidic solutions. The lowest dissolution rate value is observed in Mg-aluminoborate glasses, as a consequence of the intermediate character of magnesium which can increase the network cross-linking. For basic solutions, the chemical durability is almost constant for the different amount of alumina in the three series, likely because B₂O₃ is susceptible to nucleophilic attack, which is favored in high-OH⁻ solutions.