It is a great challenge to obtain oriented design and synthesis of new two-dimensional covalent organic frameworks (2D-COFs) with proper CN stoichiometry, N position, and band structures as specific electrocatalysts. Driven by density functional theory (DFT) calculations, we designed and synthesized a new phenazine-linked 2D-COF (COF-C 4 N) by solvothermal reaction of triphenylenehexamine (TPHA) and hexaketocyclohexane (HKH). Structural analysis confirmed that COF-C 4 N possesses an ordered crystalline structure with a highly conjugated basal plane and better stability. COF-C 4 N exhibited OER performance with a low overpotential of 349 mV at 10 mA cm −2 and a Tafel slope of 64 mV dec −1 . A combination of theoretical and experimental studies revealed that better OER performance is attributed to better crystallinity and stability, an appropriate band gap, and an N position that promotes the formation of C active sites around N atoms. The strategy of theory-driven design and targeting synthesis of 2D-COFs for OER may provide a new way to further develop metal-free materials for clean energy application.

Water buffalo is the second largest resource of milk supply around the world, and it is well known for its distinctive milk quality in terms of fat, protein, lactose, vitamin, and mineral contents. Understanding the genetic architecture of milk production traits is important for future improvement by the buffalo breeding industry. The advance of genome-wide association studies (GWAS) provides an opportunity to identify potential genetic variants affecting important economical traits. In the present study, GWAS was performed for 489 buffaloes with 1,424 lactation records using the 90K Affymetrix Buffalo SNP Array (Affymetrix/Thermo Fisher Scientific, Santa Clara, CA). Collectively, 4 candidate single nucleotide polymorphisms (SNP) in 2 genomic regions were found to associate with buffalo milk production traits. One region affecting milk fat and protein percentage was located on the equivalent of Bos taurus autosome (BTA)3, spanning 43.3 to 43.8 Mb, which harbored the most likely candidate genes MFSD14A, SLC35A3, and PALMD. The other region on the equivalent of BTA14 at 66.5 to 67.0 Mb contained candidate genes RGS22 and VPS13B and influenced buffalo total milk yield, fat yield, and protein yield. Interestingly, both of the regions were reported to have quantitative trait loci affecting milk performance in dairy cattle. Furthermore, we suggest that buffaloes with the C allele at AX-85148558 and AX-85073877 loci and the G allele at AX-85106096 locus can be selected to improve milk fat yield in this buffalo-breeding program. Meanwhile, the G allele at AX-85063131 locus can be used as the favorable allele for improving milk protein percentage. Genomic prediction showed that the reliability of genomic estimated breeding values (GEBV) of 6 milk production traits ranged from 0.06 to 0.22, and the correlation between estimated breeding values and GEBV ranged from 0.23 to 0.35. These findings provide useful information to understand the genetic basis of buffalo milk properties and may play a role in accelerating buffalo breeding programs using genomic approaches.

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