High-Throughput Computational Screening of Bioinspired Dual-Atom Alloys for CO2 Activation.

CO2 activation is an integral component of thermocatalytic and electrocatalytic CO2 conversion to liquid fuels and value-added chemicals. However, the thermodynamic stability of CO2 and the high kinetic barriers to activating CO2 are significant bottlenecks. In this work, we propose that dual atom alloys (DAAs), homo- and heterodimer islands in a Cu matrix, can offer stronger covalent CO2 binding than pristine Cu. The active site is designed to mimic the Ni-Fe anaerobic carbon monoxide dehydrogenase CO2 activation environment in a heterogeneous catalyst. We find that combinations of early transition metals (TMs) and late TMs embedded in Cu are thermodynamically stable and can offer stronger covalent CO2 binding than Cu. Additionally, we identify DAAs that have CO binding energies similar to Cu, both to avoid surface poisoning and to ensure attainable CO diffusion to Cu sites so that the C-C bond formation ability of Cu can be retained in conjunction with facile CO2 activation at the DAA sites. Machine learning feature selection reveals that the more electropositive dopants are primarily responsible for attaining the strong CO2 binding. We propose seven Cu-based DAAs and two single atom alloys (SAAs) with early TM late TM combinations, (Sc, Ag), (Y, Ag), (Y, Fe), (Y, Ru), (Y, Cd), (Y, Au), (V, Ag), (Sc), and (Y), for facile CO2 activation.

Description of drug therapy problem resolution in a statewide care management program.

OBJECTIVE: To describe drug therapy problem (DTP) resolution as part of a statewide, team-based care management program. METHODS: This was a retrospective, observational study of DTPs documented between March 1 and August 31, 2015. Data were retrieved from a Web-based platform 5 months after the observation period. DTPs were placed into groups based on the credentials of the person who documented the DTP. Next, they were identified as being documented in a transitional or nontransitional care setting. DTPs were further classified into 1 of 3 categories: medication adherence, discrepancy, or optimization. Lastly, DTP resolution was assessed. Results were analyzed using descriptive statistics. RESULTS: During the 6-month study period, 135,100 DTPs were documented, with 99% (n = 133,847) being documented by social work care managers, nurse care managers, and pharmacy staff personnel. Pharmacy staff personnel documented the majority of DTPs (51.5%), and the majority of DTPs (55%) were identified in the transitional care setting. Nurse care managers resolved more discrepancy DTPs (59.3%), whereas pharmacy staff personnel resolved more optimization DTPs (47.2%). Social work care managers resolved more medication adherence DTPs (68.6%). CONCLUSIONS: Pharmacy staff personnel primarily identified and resolved opportunities to optimize medication use, whereas nurse care managers primarily identified and resolved medication discrepancies. Social work care managers primarily identified and resolved problems related to medication adherence. When each member of the interdisciplinary care team functioned at the top of their license, all types of DTPs were effectively identified and resolved.